For best experience please turn on javascript and use a modern browser!
You are using a browser that is no longer supported by Microsoft. Please upgrade your browser. The site may not present itself correctly if you continue browsing.

Prof. dr. M. (Maarten) de Rijke

Executive Staff
Informatics Institute
Visiting address
  • Science Park 900
  • Room number: L5.56
Postal address
  • Postbus 19268
    1000 GG Amsterdam
Contact details
  • Publications

    2024

    • Deng, S., Sprangers, O., Li, M., Schelter, S., & de Rijke, M. (2024). Domain Generalization in Time Series Forecasting. ACM Transactions on Knowledge Discovery from Data, 18(5), Article 113. https://doi.org/10.1145/3643035 [details]
    • Khandel, P., Yates, A., Varbanescu, A. L., Rijke, M. D., & Pimentel, A. D. (2024). Distillation vs. Sampling for Efficient Training of Learning to Rank Models. In H. Oosterhuis, H. Bast, & C. Xiong (Eds.), Proceedings of the 2024 ACM SIGIR International Conference on Theory of Information Retrieval, ICTIR 2024, Washington, DC, USA, 13 July 2024 (pp. 51-60). ACM. https://doi.org/10.1145/3664190.3672527
    • Nguyen, T. T., Hendriksen, M. Y., Yates, A. C., & de Rijke, M. (2024). Multimodal Learned Sparse Retrieval with Probabilistic Expansion Control. In Advances in Information Retrieval: 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24–28, 2024 : proceedings (Vol. II, pp. 448–464). ( Lecture Notes in Computer Science; Vol. 14609). Springer. https://doi.org/10.48550/arXiv.2402.17535, https://doi.org/10.1007/978-3-031-56060-6_29
    • Siro, C., Aliannejadi, M., & de Rijke, M. (2024). Understanding and Predicting User Satisfaction with Conversational Recommender Systems. ACM Transactions on Information Systems, 42(2), Article 55. https://doi.org/10.1145/3624989 [details]
    • Sun, W., Guo, S., Zhang, S., Ren, P., Chen, Z., de Rijke, M., & Ren, Z. (2024). Metaphorical User Simulators for Evaluating Task-oriented Dialogue Systems. ACM Transactions on Information Systems, 42(1), Article 17. https://doi.org/10.48550/arXiv.2204.00763, https://doi.org/10.1145/3596510 [details]

    2023

    • Deffayet, R., Hager, P., Renders, J.-M., & de Rijke, M. (2023). An Offline Metric for the Debiasedness of Click Models. In SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 23-27, 2023, Taipei, Taiwan (pp. 558–568). Association for Computing Machinery. https://doi.org/10.1145/3539618.3591639 [details]
    • Deffayet, R., Renders, J-M., & de Rijke, M. (2023). Evaluating the Robustness of Click Models to Policy Distributional Shift. ACM Transactions on Information Systems, 41(4), Article 84. https://doi.org/10.1145/3569086 [details]
    • Fang, Y., Zhao, X., Chen, Y., Xiao, W., & De Rijke, M. (2023). PF-HIN:Pre-Training for Heterogeneous Information Networks. IEEE Transactions on Knowledge and Data Engineering, 35(8), 8372-8385. https://doi.org/10.1109/TKDE.2022.3206597
    • Gupta, S., Oosterhuis, H., & de Rijke, M. (2023). A Deep Generative Recommendation Method for Unbiased Learning from Implicit Feedback. In ICTIR '23: Proceedings of the 2023 ACM SIGIR International Conference on Theory of Information Retrieval : July 23, 2023, Taipei, Taiwan (pp. 87–93). Association for Computing Machinery. https://doi.org/10.1145/3578337.3605114 [details]
    • Gupta, S., Oosterhuis, H., & de Rijke, M. (2023). Safe Deployment for Counterfactual Learning to Rank with Exposure-Based Risk Minimization. In SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 23-27, 2023, Taipei, Taiwan (pp. 249–258). Association for Computing Machinery. https://doi.org/10.1145/3539618.3591760 [details]
    • Hager, P., de Rijke, M., & Zoeter, O. (2023). Contrasting Neural Click Models and Pointwise IPS Rankers. In J. Kamps, L. Goeuriot, F. Crestani, M. Maistro, H. Joho, B. Davis, C. Gurrin, U. Kruschwitz, & A. Caputo (Eds.), Advances in Information Retrieval: 45th European Conference on Information Retrieval, ECIR 2023, Dublin, Ireland, April 2–6, 2023 : proceedings (Vol. I, pp. 409-425). (Lecture Notes in Computer Science; Vol. 13980). Springer. https://doi.org/10.1007/978-3-031-28244-7_26 [details]
    • Heuss, M., Cohen, D., Mansoury, M., de Rijke, M., & Eickhoff, C. (2023). Predictive Uncertainty-based Bias Mitigation in Ranking. In CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management : October 21-25, 2023, Birmingham, England (pp. 762-772). Association for Computing Machinery. https://doi.org/10.1145/3583780.3615011 [details]
    • Jullien, S., Ariannezhad, M., Groth, P., & Rijke, M. D. (2023). A Simulation Environment and Reinforcement Learning Method for Waste Reduction. Transactions on Machine Learning Research, (4), Article 769. https://openreview.net/forum?id=KSvr8A62MD [details]
    • Ling, Y., Cai, F., Liu, J., Chen, H., & de Rijke, M. (2023). Keep and Select: Improving hierarchical context modeling for multi-turn response generation. IEEE Transactions on Neural Networks and Learning Systems, 34(7), 3636-3649. https://doi.org/10.1109/TNNLS.2021.3112700
    • Ma, M., Ren, P., Chen, Z., Ren, Z., Liang, H., Ma, J., & De Rijke, M. (2023). Improving Transformer-based Sequential Recommenders through Preference Editing. ACM Transactions on Information Systems, 41(3), Article 71. https://doi.org/10.1145/3564282
    • Meng, C., Aliannejadi, M., & de Rijke, M. (2023). Performance Prediction for Conversational Search Using Perplexities of Query Rewrites. In G. Faggioli, N. Ferro, J. Mothe, & F. Raiber (Eds.), Proceedings of the The QPP++ 2023: Query Performance Prediction and Its Evaluation in New Tasks Workshop: co-located with The 45th European Conference on Information Retrieval (ECIR) : Dublin, Ireland, April 6th, 2023 (pp. 25-28). (CEUR Workshop Proceedings; Vol. 3366). CEUR-WS. https://ceur-ws.org/Vol-3366/paper-05.pdf [details]
    • Meng, C., Aliannejadi, M., & de Rijke, M. (2023). System Initiative Prediction for Multi-turn Conversational Information Seeking. In CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management : October 21-25, 2023, Birmingham, England (pp. 1807-1817). Association for Computing Machinery. https://doi.org/10.1145/3583780.3615070 [details]
    • Meng, C., Arabzadeh, N., Aliannejadi, M., & de Rijke, M. (2023). Query Performance Prediction: From Ad-hoc to Conversational Search. In SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 23-27, 2023, Taipei, Taiwan (pp. 2583-2593). Association for Computing Machinery. https://doi.org/10.1145/3539618.3591919 [details]
    • Pal, V., Yates, A., Kanoulas, E., & de Rijke, M. (2023). MultiTabQA: Generating Tabular Answers for Multi-Table Question Answering. In A. Rogers, J. Boyd-Graber, & N. Okazaki (Eds.), The 61st Conference of the Association for Computational Linguistics: Proceedings of the Conference : ACL 2023 : July 9-14, 2023 (Vol. 1, pp. 6322–6334). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.acl-long.348 [details]
    • Rajapakse, T. C., & de Rijke, M. (2023). Improving the Generalizability of the Dense Passage Retriever. In J. Kamps, L. Goeuriot, F. Crestani, M. Maistro, H. Joho, B. Davis, C. Gurrin, U. Kruschwitz, & A. Caputo (Eds.), Advances in Information Retrieval: 45th European Conference on Information Retrieval, ECIR 2023, Dublin, Ireland, April 2–6, 2023 : proceedings (Vol. II, pp. 94-109). (Lecture Notes in Computer Science; Vol. 13981). Springer. https://doi.org/10.1007/978-3-031-28238-6_7 [details]
    • Sarvi, F., Aliannejadi, M., Schelter, S., & de Rijke, M. (2023). How to Make an Outlier? Studying the Effect of Presentational Features on the Outlierness of Items in Product Search Results. In CHIIR'23: proceedings of the 2023 Conference on Human Information Interaction and Retrieval : March 19-23, 2023, Austin, Texas, USA (pp. 346-350). The Association for Computing Machinery. https://doi.org/10.1145/3576840.3578278 [details]
    • Sarvi, F., Vardasbi, A., Aliannejadi, M., Schelter, S., & de Rijke, M. (2023). On the Impact of Outlier Bias on User Clicks. In SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 23-27, 2023, Taipei, Taiwan (pp. 18-27). Association for Computing Machinery. https://doi.org/10.1145/3539618.3591745 [details]
    • Sprangers, O., Schelter, S., & de Rijke, M. (2023). Parameter Efficient Deep Probabilistic Forecasting. International Journal of Forecasting, 39(1), 332-345. https://doi.org/10.1016/j.ijforecast.2021.11.011 [details]
    • Wu, C., Zhang, R., Guo, J., de Rijke, M., Fan, Y., & Cheng, X. (2023). PRADA: Practical Black-Box Adversarial Attacks against Neural Ranking Models. ACM Transactions on Information Systems, 41(4), Article 89. https://doi.org/10.1145/3576923

    2022

    • Ariannezhad, M., Jullien, S., Li, M., Fang, M., Schelter, S., & de Rijke, M. (2022). ReCANet: A Repeat Consumption-Aware Neural Network for Next Basket Recommendation in Grocery Shopping. In SIGIR '22: proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2022, Madrid, Spain (pp. 1240-1250). The Association for Computing Machinery. https://doi.org/10.1145/3477495.3531708 [details]
    • Ariannezhad, M., Yahya, M., Meij, E., Schelter, S., & de Rijke, M. (2022). Understanding Financial Information Seeking Behavior from User Interactions with Company Filings. In WWW '22 Companion: companion proceedings of the Web Conference 2022: April 25, 2022, Lyon, France (pp. 586-594). Association for Computing Machinery. https://doi.org/10.1145/3487553.3524636 [details]
    • Bleeker, M., & de Rijke, M. (2022). Do Lessons from Metric Learning Generalize to Image-Caption Retrieval? In M. Hagen, S. Verberne, C. Macdonald, C. Seifert, K. Balog, K. Nørvåg, & V. Setty (Eds.), Advances in Information Retrieval: 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022 : proceedings (Vol. I, pp. 535-551). (Lecture Notes in Computer Science; Vol. 13185). Springer. https://doi.org/10.1007/978-3-030-99736-6_36 [details]
    • Bénédict, G., Koops, H. V., Odijk, D., & de Rijke, M. (2022). sigmoidF1: A Smooth F1 Score Surrogate Loss for Multilabel Classification. Transactions on Machine Learning Research, Article 148. https://doi.org/10.48550/arXiv.2108.10566 [details]
    • Chen, W., Ren, P., Cai, F., Sun, F., & de Rijke, M. (2022). Multi-interest Diversification for End-to-end Sequential Recommendation. ACM Transactions on Information Systems, 40(1), Article 20. Advance online publication. https://doi.org/10.1145/3475768 [details]
    • Chen, Y., Wang, Y., Ren, P., Wang, M., & de Rijke, M. (2022). Bayesian Feature Interaction Selection for Factorization Machines. Artificial Intelligence, 302, Article 103589. https://doi.org/10.1016/j.artint.2021.103589 [details]
    • Deffayet, R., Thonet, T., Renders, J-M., & de Rijke, M. (2022). Offline Evaluation for Reinforcement Learning-based Recommendation: A Critical Issue and Some Alternatives. SIGIR Forum, 56(2), Article 3. https://doi.org/10.1145/3582900.3582905 [details]
    • Fang, J., Liang, S., Meng, Z., & de Rijke, M. (2022). Hyperspherical Variational Co-embedding for Attributed Networks. ACM Transactions on Information Systems, 40(3), Article 58. https://doi.org/10.1145/3478284 [details]
    • Fang, Y., Zhao, X., Huang, P., Xiao, W., & de Rijke, M. (2022). Scalable Representation Learning for Dynamic Heterogeneous Information Networks via Metagraphs. ACM Transactions on Information Systems, 40(4), Article 64. https://doi.org/10.1145/3485189 [details]
    • Hendriksen, M., Bleeker, M., Vakulenko, S., van Noord, N., Kuiper, E., & de Rijke, M. (2022). Extending CLIP for Category-to-Image Retrieval in E-Commerce. In M. Hagen, S. Verberne, C. Macdonald, C. Seifert, K. Balog, K. Nørvåg, & V. Setty (Eds.), Advances in Information Retrieval: 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022 : proceedings (Vol. I, pp. 289-303). (Lecture Notes in Computer Science; Vol. 13185). Springer. https://doi.org/10.1007/978-3-030-99736-6_20 [details]
    • Huang, J., Oosterhuis, H., & de Rijke, M. (2022). It Is Different When Items Are Older: Debiasing Recommendations When Selection Bias and User Preferences Are Dynamic. In WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining : February 21-25, 2022 : virtual event, Tempe, AZ, USA (pp. 381–389). Association for Computing Machinery. https://doi.org/10.1145/3488560.3498375 [details]
    • Huang, J., Oosterhuis, H., Cetinkaya, B., Rood, T., & de Rijke, M. (2022). State Encoders in Reinforcement Learning for Recommendation: A Reproducibility Study. In SIGIR '22: proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2022, Madrid, Spain (pp. 2738-2748). The Association for Computing Machinery. https://doi.org/10.1145/3477495.3531716 [details]
    • Kale, A., Kallumadi, S., King, T. H., Malmasi, S., de Rijke, M., & Tagliabue, J. (2022). eCom'22: The SIGIR 2022 Workshop on eCommerce. In SIGIR '22: proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2022, Madrid, Spain (pp. 3485-3487). The Association for Computing Machinery. https://doi.org/10.1145/3477495.3531701 [details]
    • Liang, S., Pan, Z., Liu, W., Yin, J., & de Rijke, M. (2022). A Survey on Variational Autoencoders in Recommender Systems. ACM Computing Surveys.
    • Lippe, P., Ren, P., Haned, H., Voorn, B., & de Rijke, M. (2022). Simultaneously Improving Utility and User Experience in Task-oriented Dialogue Systems. In eCom 2022: The SIGIR 2022 SIGIR Workshop on eCommerce ACM. https://sigir-ecom.github.io/ecom22Papers/paper_5042.pdf
    • Lucic, A., Bleeker, M., Jullien, S., Bhargav, S., & de Rijke, M. (2022). Reproducibility as a Mechanism for Teaching Fairness, Accountability, Confidentiality, and Transparency in Artificial Intelligence. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12792-12800. https://doi.org/10.1609/aaai.v36i11.21558 [details]
    • Lucic, A., Bleeker, M., de Rijke, M., Sinha, K., Jullien, S., & Stojnic, R. (2022). Towards Reproducible Machine Learning Research in Information Retrieval. In SIGIR '22: proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2022, Madrid, Spain The Association for Computing Machinery.
    • Pal, V., Kanoulas, E., & de Rijke, M. (2022). Parameter-Efficient Abstractive Question Answering over Tables or Text. In S. Feng, H. Wan, C. Yuan, & H. Yu (Eds.), Proceedings of the Second DialDoc Workshop on Document-grounded Dialogue and Conversational Question Answering: proceedings of the workshop : DialDoc 2022 : May 26, 2022 (pp. 41–53). Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.dialdoc-1.5 [details]
    • Ren, Z., Tian, Z., Li, D., Ren, P., Yang, L., Xin, X., Liang, H., de Rijke, M., & Chen, Z. (2022). Variational Reasoning about User Preferences for Conversational Recommendation. In SIGIR '22: proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2022, Madrid, Spain The Association for Computing Machinery.
    • Sarvi, F., Heuss, M., Aliannejadi, M., Schelter, S., & de Rijke, M. (2022). Understanding and Mitigating the Effect of Outliers in Fair Ranking. In WSDM '22: Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining : February 21-25, 2022 : virtual event, Tempe, AZ, USA (pp. 861-869). Association for Computing Machinery. https://doi.org/10.1145/3488560.3498441 [details]
    • Siro, C., Aliannejadi, M., & de Rijke, M. (2022). Understanding User Satisfaction with Task-oriented Dialogue Systems. In SIGIR '22: proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2022, Madrid, Spain (pp. 2018-2023). The Association for Computing Machinery. https://doi.org/10.1145/3477495.3531798 [details]
    • Vardasbi, A., Sarvi, F., & de Rijke, M. (2022). Probabilistic Permutation Graph Search: Black-Box Optimization for Fairness in Ranking. In SIGIR '22: proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2022, Madrid, Spain The Association for Computing Machinery.
    • Vardasbi, A., de Rijke, M., & Dehghani, M. (2022). Intersection of Parallels as an Early Stopping Criterion. In CIKM '22: proceedings of the 31st ACM International Conference on Information & Knowledge Management : October 17-21, 2022, Atlanta, GA, USA (pp. 1965-1974). The Association for Computing Machinery. https://doi.org/10.1145/3511808.3557366 [details]
    • Vrijenhoek, S., Bénédict, G., Gutierrez Granada, M., Odijk, D., & de Rijke, M. (2022). RADio - Rank-Aware Divergence Metrics to Measure Normative Diversity in News Recommendations. In RecSys' 22: Proceedings of the Sixteenth ACM Conference on Recommender Systems : Seattle, WA, USA, September 18-23, 2022 (pp. 208-219). Association for Computing Machinery. https://doi.org/10.1145/3523227.3546780 [details]
    • Wang, Z., Huang, N., Sun, F., Ren, P., Chen, Z., Luo, H., de Rijke, M., & Ren, Z. (2022). Debiasing Learning for Membership Inference Attacks Against Recommender Systems. In KDD '22: Proceedings of the 28th Conference on Knowledge Discovery and Data Mining ACM.
    • Wu, C., Zhang, R., Guo, J., Chen, W., Fan, Y., de Rijke, M., & Cheng, X. (2022). Certified Robustness to Word Substitution Ranking Attack for Neural Ranking Models. In CIKM '22: proceedings of the 31st ACM International Conference on Information & Knowledge Management : October 17-21, 2022, Atlanta, GA, USA (pp. 2128-2137). The Association for Computing Machinery. https://doi.org/10.1145/3511808.3557256 [details]
    • Yan, G., Pei, J., Ren, P., Ren, Z., Xin, X., Liang, H., de Rijke, M., & Chen, Z. (2022). ReMeDi: Resources for Multi-domain, Multi-service, Medical Dialogues. In SIGIR '22: proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2022, Madrid, Spain The Association for Computing Machinery.
    • Zhang, Y., Ren, P., Deng, W., Chen, Z., & de Rijke, M. (2022). Improving Multi-label Malevolence Detection in Dialogues through Multi-faceted Label Correlation Enhancement. In S. Muresan, P. Nakov, & A. Villavicencio (Eds.), The 60th Annual Meeting of the Association for Computational Linguistics: ACL 2022 : proceedings of the conference : May 22-27, 2022 (Vol. 1, pp. 3543–3555). Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.acl-long.248 [details]
    • Zhao, M., Yang, Y., Li, M., Wang, J., Wu, W., Ren, P., de Rijke, M., & Ren, Z. (2022). Personalized Abstractive Opinion Tagging. In SIGIR '22: proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2022, Madrid, Spain The Association for Computing Machinery.
    • ter Hoeve, M., Kiseleva, J., & de Rijke, M. (2022). What Makes a Good and Useful Summary? Incorporating Users in Automatic Summarization Research. In NAACL 2022: 2022 Conference of the North American Chapter of the Association for Computational Linguistics ACL.

    2021

    • Ariannezhad, M., Jullien, S., Nauts, P., Fang, M., Schelter, S., & de Rijke, M. (2021). Understanding Multi-Channel Customer Behavior in Retail. In CIKM '21: proceedings of the 30th ACM International Conference on Information & Knowledge Management : November 1-5, 2021, virtual event, Australia (pp. 2867–2871). The Association for Computing Machinery. https://doi.org/10.1145/3459637.3482208 [details]
    • Cheng, Q., Ren, Z., Lin, Y., Ren, P., Chen, Z., Liu, X., & de Rijke, M. (2021). Long Short-term Session Search: Joint Personalized Reranking and Next Query Prediction. In The Web Conference 2021: proceedings of the World Wide Web Conference WWW 2021 : April 19-23, 2021, Ljubljana, Slovenia (pp. 239-248). Association for Computing Machinery. https://doi.org/10.1145/3442381.3449941 [details]
    • Gao, C., Lei, W., He, X., de Rijke, M., & Chua, T-S. (2021). Advances and Challenges in Conversational Recommender Systems: A Survey. AI open, 2, 100-126. Advance online publication. https://doi.org/10.1016/j.aiopen.2021.06.002 [details]
    • Goei, K., Hendriksen, M., & de Rijke, M. (2021). Tackling Attribute Fine-grainedness in Cross-modal Fashion Search with Multi-level Features. In Proceedings of the 2021 SIGIR Workshop on eCommerce (SIGIR eCom’20): July 15, 2021, Virtual Event, Montreal, Canada Article workshop paper 3 ACM. https://sigir-ecom.github.io/ecom21Papers/paper16.pdf [details]
    • Kallumadi, S., King, T. H., Malmasi, S., & de Rijke, M. (2021). ECOM’21: The SIGIR 2021 Workshop on eCommerce. In SIGIR '21: proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2021, virtual event, Canada (pp. 2685-2688). Association for Computing Machinery. https://doi.org/10.1145/3404835.3462820 [details]
    • Li, D., Ren, Z., Ren, P., Chen, Z., Fan, M., Ma, J., & de Rijke, M. (2021). Semi-supervised Variational Reasoning for Medical Dialogue Generation. In SIGIR '21: proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2021, virtual event, Canada (pp. 544-554). Association for Computing Machinery. https://doi.org/10.1145/3404835.3462921 [details]
    • Li, Q., Li, P., Li, X., Ren, Z., Chen, Z., & de Rijke, M. (2021). Abstractive Opinion Tagging. In WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data Mining : March 8-12, 2021, virtual event, Israel (pp. 337-345). Association for Computing Machinery. https://doi.org/10.1145/3437963.3441804 [details]
    • Li, X., de Rijke, M., Liu, Y., Mao, J., Ma, W., Zhang, M., & Ma, S. (2021). Investigating Session Search Behavior with Knowledge Graphs. In SIGIR '21: proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2021, virtual event, Canada (pp. 1708-1712). Association for Computing Machinery. https://doi.org/10.1145/3404835.3463107 [details]
    • Li, Z., Kiseleva, Y., & de Rijke, M. (2021). Improving Response Quality with Backward Reasoning in Open-domain Dialogue Systems. In SIGIR '21: proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2021, virtual event, Canada (pp. 1940-1944). Association for Computing Machinery. https://doi.org/10.1145/3404835.3463004 [details]
    • Liu, Z., Ren, P., Chen, Z., Ren, Z., de Rijke, M., & Zhou, M. (2021). Learning to Ask Conversational Questions by Optimizing Levenshtein Distance. In C. Zong, F. Xia, W. Li, & R. Navigli (Eds.), The 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: ACL-IJCNLP 2021 : proceedings of the conference : August 1-6, 2021 (Vol. 1, pp. 5638-5650). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.acl-long.438 [details]
    • Lu, H., Ma, W., Zhang, M., de Rijke, M., Liu, Y., & Ma, S. (2021). Standing in Your Shoes: External Assessments for Personalized Recommender Systems. In SIGIR '21: proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2021, virtual event, Canada (pp. 1523-1533). Association for Computing Machinery. https://doi.org/10.1145/3404835.3462916 [details]
    • Lucic, A., ter Hoeve, M., Tolomei, G., de Rijke, M., & Silvestri, F. (2021). CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks. In DLG-KDD’21: Deep Learning on Graphs, August 14–18, 2021, Online Article 3 ACM. https://doi.org/10.1145/1122445.1122456 [details]
    • Meng, C., Ren, P., Chen, Z., Ren, Z., Xi, T., & de Rijke, M. (2021). Initiative-Aware Self-Supervised Learning for Knowledge-Grounded Conversations. In SIGIR '21: proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2021, virtual event, Canada (pp. 522-532). Association for Computing Machinery. https://doi.org/10.1145/3404835.3462824 [details]
    • Oosterhuis, H., & de Rijke, M. (2021). Robust Generalization and Safe Query-specialization in Counterfactual Learning to Rank. In The Web Conference 2021: proceedings of the World Wide Web Conference WWW 2021 : April 19-23, 2021, Ljubljana, Slovenia (pp. 158-170). Association for Computing Machinery. https://doi.org/10.1145/3442381.3450018 [details]
    • Oosterhuis, H., & de Rijke, M. (2021). Unifying Online and Counterfactual Learning to Rank: A Novel Counterfactual Estimator that Effectively Utilizes Online Interventions. In WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data Mining : March 8-12, 2021, virtual event, Israel (pp. 463-471). Association for Computing Machinery. https://doi.org/10.1145/3437963.3441794 [details]
    • Pei, J., Ren, P., & de Rijke, M. (2021). A Cooperative Memory Network for Personalized Task-oriented Dialogue Systems with Incomplete User Profiles. In The Web Conference 2021: proceedings of the World Wide Web Conference WWW 2021 : April 19-23, 2021, Ljubljana, Slovenia (pp. 1552-1561). Association for Computing Machinery. https://doi.org/10.1145/3442381.3449843 [details]
    • Ren, P., Chen, Z., Ren, Z., Kanoulas, E., Monz, C., & de Rijke, M. (2021). Conversations with Search Engines: SERP-based Conversational Response Generation. ACM Transactions on Information Systems, 39(4), Article 47. https://doi.org/10.1145/3432726 [details]
    • Ren, P., Liu, Z., Song, X., Tian, H., Chen, Z., Ren, Z., & de Rijke, M. (2021). Wizard of Search Engine: Access to Information Through Conversations with Search Engines. In SIGIR '21: proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2021, virtual event, Canada (pp. 533-543). Association for Computing Machinery. https://doi.org/10.1145/3404835.3462897 [details]
    • Sepliarskaia, A., Genc, S., & de Rijke, M. (2021). A Deep Reinforcement Learning-Based Approach to Query-Free Interactive Target Item Retrieval. In Proceedings of the 2021 SIGIR Workshop on eCommerce (SIGIR eCom’20): July 15, 2021, Virtual Event, Montreal, Canada Article workshop paper 1 ACM. https://sigir-ecom.github.io/ecom21Papers/paper2.pdf [details]
    • Sepliarskaia, A., Kiseleva, Y., & de Rijke, M. (2021). How Not to Measure Disentanglement. In ICML Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI
    • Sprangers, O., Schelter, S., & de Rijke, M. (2021). Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression. In KDD ’21: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining : August 14-18, 2021, virtual event, Singapore (pp. 1510-1520). Association for Computing Machinery. https://doi.org/10.1145/3447548.3467278 [details]
    • Sun, W., Meng, C., Meng, Q., Ren, Z., Ren, P., Chen, Z., & de Rijke, M. (2021). Conversations Powered by Cross-Lingual Knowledge. In SIGIR '21: proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2021, virtual event, Canada (pp. 1442-1451). Association for Computing Machinery. https://doi.org/10.1145/3404835.3462883 [details]
    • Sun, W., Zhang, S., Balog, K., Ren, Z., Ren, P., Chen, Z., & de Rijke, M. (2021). Simulating User Satisfaction for the Evaluation of Task-oriented Dialogue Systems. In SIGIR '21: proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2021, virtual event, Canada (pp. 2499-2506). Association for Computing Machinery. https://doi.org/10.1145/3404835.3463241 [details]
    • Vakulenko, S., Kanoulas, E., & de Rijke, M. (2021). A Large-Scale Analysis of Mixed Initiative in Information-Seeking Dialogues for Conversational Search. ACM Transactions on Information Systems, 39(4), Article 49. Advance online publication. https://doi.org/10.1145/3466796 [details]
    • Voskarides, N., Meij, E., Sauer, S., & de Rijke, M. (2021). News Article Retrieval in Context for Event-centric Narrative Creation. In ICTIR '21: Proceedings of the 2021 ACM SIGIR International Conference on Theory of Information Retrieval : July 11, 2021, virtual event, Canada (pp. 103-112). Association for Computing Machinery. https://doi.org/10.1145/3471158.3472247 [details]
    • Wang, Z., Song, H., Ren, Z., Ren, P., Chen, Z., Liu, X., Li, H., & de Rijke, M. (2021). Cross-Domain Contract Element Extraction with a Bi-directional Feedback Clause-Element Relation Network. In SIGIR '21: proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2021, virtual event, Canada (pp. 1003-1012). Association for Computing Machinery. https://doi.org/10.1145/3404835.3462873 [details]
    • Zhang, Y., Ren, P., & de Rijke, M. (2021). A Human-machine Collaborative Framework for Evaluating Malevolence in Dialogues. In C. Zong, F. Xia, W. Li, & R. Navigli (Eds.), The 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: ACL-IJCNLP 2021 : proceedings of the conference : August 1-6, 2021 (Vol. 1, pp. 5612–5623). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.acl-long.436 [details]
    • Zhang, Y., Ren, P., & de Rijke, M. (2021). A Taxonomy, Dataset and Benchmark for Detecting and Classifying Malevolent Dialogue Responses. Journal of the Association for Information Science and Technology, 72(12), 1477-1497. Advance online publication. https://doi.org/10.1002/asi.24496 [details]

    2020

    • Akata, Z., Balliet, D., de Rijke, M., Dignum, F., Dignum, V., Eiben, G., Fokkens, A., Grossi, D., Hindriks, K., Hoos, H., Hung, H., Jonker, C., Monz, C., Neerincx, M., Oliehoek, F., Prakken, H., Schlobach, S., van der Gaag, L., van Harmelen, F., ... Welling, M. (2020). A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence. Computer, 53(8), 18-28. https://doi.org/10.1109/MC.2020.2996587 [details]
    • Ariannezhad, M., Schelter, S., & de Rijke, M. (2020). Demand Forecasting in the Presence of Privileged Information. In V. Lemaire, S. Malinowski, A. Bagnall, T. Guyet, R. Tavenard, & G. Ifrim (Eds.), Advanced Analytics and Learning on Temporal Data: 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020 : revised selected papers (pp. 46-62). (Lecture Notes in Computer Science; Vol. 12588), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-030-65742-0_4 [details]
    • Bleeker, M., & de Rijke, M. (2020). Bidirectional Scene Text Recognition with a Single Decoder. In G. De Giacomo, A. Catala, B. Dilkina, M. Milano, S. Barro, A. Bugarín, & J. Lang (Eds.), ECAI 2020: 24th European Conference on Artificial Intelligence : 29 August-8 September 2020, Santiago de Compostela, Spain, including 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020) : proceedings (pp. 2664–2671). (Frontiers in Artificial Intelligence and Applications; Vol. 325). IOS Press. https://doi.org/10.3233/FAIA200404 [details]
    • Chen, W., Cai, F., Chen, H., & de Rijke, M. (2020). Hierarchical Neural Query Suggestion with an Attention Mechanism. Information Processing and Management, 57(6), Article 102040. https://doi.org/10.1016/j.ipm.2019.05.001 [details]
    • Chen, W., Cai, F., Chen, H., & de Rijke, M. (2020). Personalized Query Suggestion Diversification in Information Retrieval. Frontiers of Computer Science, 14(3), Article 143602. Advance online publication. https://doi.org/10.1007/s11704-018-7283-x [details]
    • Chen, W., Ren, P., Cai, F., Sun, F., & de Rijke, M. (2020). Improving End-to-End Sequential Recommendations with Intent-aware Diversification. In CIKM '20: proceedings of the 29th ACM International Conference on Information & Knowledge Management : October 19-23, 2020, Virtual Event, Ireland (pp. 175–184). The Association for Computing Machinery. https://doi.org/10.1145/3340531.3411897 [details]
    • Chen, Y., Wang, Y., Zhao, X., Yin, H., Markov, I., & De Rijke, M. (2020). Local Variational Feature-Based Similarity Models for Recommending Top-N New Items. ACM Transactions on Information Systems, 38(2), Article 12. https://doi.org/10.1145/3372154 [details]
    • Chen, Y., Wang, Y., Zhao, X., Zou, J., & de Rijke, M. (2020). Block-Aware Item Similarity Models for Top-N Recommendation. ACM Transactions on Information Systems, 38(4), Article 42. Advance online publication. https://doi.org/10.1145/3411754 [details]
    • Hendriksen, M., Kuiper, E., Nauts, P., Schelter, S., & de Rijke, M. (2020). Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers. In The 2020 SIGIR Workshop On eCommerce: July 30 : accepted papers Article 23 SIGIR eCom'20. https://sigir-ecom.github.io/ecom20Papers/paper23.pdf [details]
    • Huang, J., Oosterhuis, H., de Rijke, M., & van Hoof, H. (2020). Keeping Dataset Biases out of the Simulation: A Debiased Simulator for Reinforcement Learning based Recommender Systems. In RECSYS 2020: 14th ACM Conference on Recommender Systems : Virtual Event, Brazil, September 22-26, 2020 (pp. 190–199). The Association for Computing Machinery. https://doi.org/10.1145/3383313.3412252 [details]
    • Jagerman, R., & de Rijke, M. (2020). Accelerated Convergence for Counterfactual Learning to Rank. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 469–478). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401069 [details]
    • Jagerman, R., Markov, I., & de Rijke, M. (2020). Safe Exploration for Optimizing Contextual Bandits. ACM Transactions on Information Systems, 38(3), Article 24. Advance online publication. https://doi.org/10.1145/3385670 [details]
    • Lei, W., He, X., de Rijke, M., & Chua, T-S. (2020). Conversational Recommendation: Formulation, Methods, and Evaluation. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 2425–2428). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401419 [details]
    • Li, C., Feng, H., & de Rijke, M. (2020). Cascading Hybrid Bandits: Online Learning to Rank for Relevance and Diversity. In RECSYS 2020: 14th ACM Conference on Recommender Systems : Virtual Event, Brazil, September 22-26, 2020 (pp. 33–42). The Association for Computing Machinery. https://doi.org/10.1145/3383313.3412245 [details]
    • Li, C., Markov, I., de Rijke, M., & Zoghi, M. (2020). MergeDTS: A Method for Effective Large-scale Online Ranker Evaluation. ACM Transactions on Information Systems, 38(4), Article 40. Advance online publication. https://doi.org/10.1145/3411753 [details]
    • Li, X., de Rijke, M., Liu, Y., Mao, J., Ma, W., Zhang, M., & Ma, S. (2020). Learning Better Representations for Neural Information Retrieval with Graph Information. In CIKM '20: proceedings of the 29th ACM International Conference on Information & Knowledge Management : October 19-23, 2020, Virtual Event, Ireland (pp. 795-804). The Association for Computing Machinery. https://doi.org/10.1145/3340531.3411957 [details]
    • Li, Z., Kiseleva, J., & de Rijke, M. (2020). Rethinking Supervised Learning and Reinforcement Learning in Task-Oriented Dialogue Systems. In T. Cohn, Y. He, & Y. Liu (Eds.), Findings of the Association for Computational Linguistics. Findings of ACL: EMNLP 2020: 16-20 November, 2020 (pp. 3537–3546). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.findings-emnlp.316 [details]
    • Li, Z., Lee, S., Peng, B., Li, J., Kiseleva, J., de Rijke, M., Shayandeh, S., & Gao, J. (2020). Guided Dialogue Policy Learning without Adversarial Learning in the Loop. In T. Cohn, Y. He, & Y. Liu (Eds.), Findings of the Association for Computational Linguistics. Findings of ACL: EMNLP 2020: 16-20 November, 2020 (pp. 2308–2317). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.findings-emnlp.209 [details]
    • Lin, Y., Ren, P., Chen, Z., Ren, Z., Ma, J., & de Rijke, M. (2020). Explainable Outfit Recommendation with Joint Outfit Matching and Comment Generation. IEEE Transactions on Knowledge & Data Engineering, 32(8), 1502-1516. Advance online publication. https://doi.org/10.1109/TKDE.2019.2906190 [details]
    • Lin, Y., Ren, P., Chen, Z., Ren, Z., Yu, D., Ma, J., de Rijke, M., & Cheng, X. (2020). Meta Matrix Factorization for Federated Rating Predictions. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 981–990). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401081 [details]
    • Ling, Y., Cai, F., Chen, H., & de Rijke, M. (2020). Leveraging Context for Neural Question Generation in Open-domain Dialogue Systems. In The Web Conference 2020: proceedings of the World Wide Web Conference WWW 2020 : Taipei 2020 : April 20-24, 2020, Taipei, Taiwan (pp. 2486–2492). International World Wide Web Conference Committee. https://doi.org/10.1145/3366423.3379996 [details]
    • Lucic, A., Haned, H., & de Rijke, M. (2020). Why Does My Model Fail? Contrastive Local Explanations for Retail Forecasting. In FAT* '20: proceedings of the 2020 Conference on Fairness, Accountability, and Transparency : January 27-30, 2020, Barcelona, Spain (pp. 90-98). The Association for Computing Machinery. https://doi.org/10.1145/3351095.3372824 [details]
    • Meng, C., Ren, P., Chen, Z., Monz, C., Ma, J., & de Rijke, M. (2020). RefNet: A Reference-Aware Network for Background Based Conversation. In AAAI-20, IAAI-20, EAAI-20 proceedings: Thirty-Fourth AAAI Conference on Artificial Intelligence, Thirty-Second Conference on Innovative Applications of Artificial Intelligence, The Tenth Symposium on Educational Advances in Artificial Intelligence : February 7–12th, 2020, New York Hilton Midtown, New York, New York, USA (Vol. 5, pp. 8496-8503). (Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 34). AAAI Press. https://doi.org/10.1609/aaai.v34i05.6370 [details]
    • Meng, C., Ren, P., Chen, Z., Sun, W., Ren, Z., Tu, Z., & de Rijke, M. (2020). DukeNet: A Dual Knowledge Interaction Network for Knowledge-Grounded Conversation. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 1151–1160). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401097 [details]
    • Oosterhuis, H., & de Rijke, M. (2020). Policy-Aware Unbiased Learning to Rank for Top-k Rankings. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 489–498). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401102 [details]
    • Oosterhuis, H., & de Rijke, M. (2020). Taking the Counterfactual Online: Efficient and Unbiased Online Evaluation for Ranking. In ICTIR'20: proceedings of the 2020 ACM SIGIR International Conference on Theory of Information Retrieval : September 14-17, 2020, Virtual Event, Norway (pp. 137–144). The Association for Computing Machinery. https://doi.org/10.1145/3409256.3409820 [details]
    • Oosterhuis, H., Jagerman, R., & de Rijke, M. (2020). Unbiased Learning to Rank: Counterfactual and Online Approaches. In The Web Conference 2020: companion of the World Wide Web Conference WWW 2020 : Taipei 2020 : April 20-24, 2020, Taipei, Taiwan (pp. 299-300). International World Wide Web Conference Committee. https://doi.org/10.1145/3366424.3383107 [details]
    • Pan, Z., Cai, F., Chen, W., Chen, H., & de Rijke, M. (2020). Star Graph Neural Networks for Session-based Recommendation. In CIKM '20: proceedings of the 29th ACM International Conference on Information & Knowledge Management : October 19-23, 2020, Virtual Event, Ireland (pp. 1195–1204). The Association for Computing Machinery. https://doi.org/10.1145/3340531.3412014 [details]
    • Pan, Z., Cai, F., Ling, Y., & de Rijke, M. (2020). An Intent-guided Collaborative Machine for Session-based Recommendation. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 1833-1836). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401273 [details]
    • Pan, Z., Cai, F., Ling, Y., & de Rijke, M. (2020). Rethinking Item Importance in Session-based Recommendation. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 1837-1840). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401274 [details]
    • Pei, J., Ren, P., Monz, C., & de Rijke, M. (2020). Retrospective and Prospective Mixture-of-Generators for Task-oriented Dialogue Response Generation. In G. De Giacomo, A. Catala, B. Dilkina, M. Milano, S. Barro, A. Bugarín, & J. Lang (Eds.), ECAI 2020: 24th European Conference on Artificial Intelligence : 29 August-8 September 2020, Santiago de Compostela, Spain, including 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020) : proceedings (pp. 2148-2155). ( Frontiers in Artificial Intelligence and Applications; Vol. 325). IOS Press. https://doi.org/10.3233/FAIA200339 [details]
    • Reinanda, R., Meij, E., & de Rijke, M. (2020). Knowledge Graphs: An Information Retrieval Perspective. Foundations and Trends in Information Retrieval, 14(4), 289-444. https://doi.org/10.1561/1500000063 [details]
    • Ren, P., Chen, Z., Monz, C., Ma, J., & de Rijke, M. (2020). Thinking Globally, Acting Locally: Distantly Supervised Global-to-Local Knowledge Selection for Background Based Conversation. In AAAI-20, IAAI-20, EAAI-20 proceedings: Thirty-Fourth AAAI Conference on Artificial Intelligence, Thirty-Second Conference on Innovative Applications of Artificial Intelligence, The Tenth Symposium on Educational Advances in Artificial Intelligence : February 7–12th, 2020, New York Hilton Midtown, New York, New York, USA (Vol. 5, pp. 8697-8704). (Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 34). AAAI Press. https://doi.org/10.1609/aaai.v34i05.6395 [details]
    • Ren, P., Ren, Z., Sun, F., He, X., Yin, D., & de Rijke, M. (2020). NLP4REC: The WSDM 2020 Workshop on Natural Language Processing for Recommendations. In WSDM '20: proceedings of the 13th International Conference on Web Search and Data Mining : February 3-7, 2020, Houston, TX, USA (pp. 907-908). Association for Computing Machinery. https://doi.org/10.1145/3336191.3371884 [details]
    • Sarvi, F., Voskarides, N., Mooiman, L., Schelter, S., & de Rijke, M. (2020). A Comparison of Supervised Learning to Match Methods for Product Search. In The 2020 SIGIR Workshop On eCommerce: July 30 : accepted papers Article 30 SIGIR eCom'20. https://sigir-ecom.github.io/ecom20Papers/paper30.pdf [details]
    • Steenvoorden, A., Di Gloria, E., Chen, W., Ren, P., & de Rijke, M. (2020). Attribute-aware Diversification for Sequential Recommendations. In AIIS 2020: The SIGIR 2020 Workshop on Applied Interactive Information Systems : held in conjunction with SIGIR'20 July 30, 2020, Xi'an, China Article 1 AIIS Workshop. https://aiis.newidea.fun/papers/AIIS_2020_paper_1.pdf [details]
    • Tsagkias, M., King, T. H., Kallumadi, S., Murdock, V., & de Rijke, M. (2020). Challenges and Research Opportunities in eCommerce Search and Recommendations. SIGIR Forum, 54(1), Article 2. https://doi.org/10.1145/3451964.3451966 [details]
    • Vakulenko, S., Kanoulas, E., & de Rijke, M. (2020). An Analysis of Mixed Initiative and Collaboration in Information-Seeking Dialogues. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 2085-2088). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401297 [details]
    • Vardasbi, A., Oosterhuis, H., & de Rijke, M. (2020). When Inverse Propensity Scoring does not Work: Affine Corrections for Unbiased Learning to Rank. In CIKM '20: proceedings of the 29th ACM International Conference on Information & Knowledge Management : October 19-23, 2020, Virtual Event, Ireland (pp. 1475–1484). The Association for Computing Machinery. https://doi.org/10.1145/3340531.3412031 [details]
    • Vardasbi, A., de Rijke, M., & Markov, I. (2020). Cascade Model-based Propensity Estimation for Counterfactual Learning to Rank. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 2089-2092). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401299 [details]
    • Voskarides, N., Li, D., Ren, P., Kanoulas, E., & de Rijke, M. (2020). Query Resolution for Conversational Search with Limited Supervision. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 921-930). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401130 [details]
    • Wang, S., Ren, P., Chen, Z., Ren, Z., Nie, J-Y., Ma, J., & de Rijke, M. (2020). Coding Electronic Health Records with Adversarial Reinforcement Path Generation. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 801–810). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401135 [details]
    • Wu, C., Kanoulas, E., & de Rijke, M. (2020). It All Starts with Entities: A Salient Entity Topic Model. Natural Language Engineering, 26(5), 531-549. Advance online publication. https://doi.org/10.1017/S1351324919000585 [details]
    • Wu, C., Kanoulas, E., & de Rijke, M. (2020). Learning entity-centric document representations using an entity facet topic model. Information Processing and Management, 57(3), Article 102216. https://doi.org/10.1016/j.ipm.2020.102216 [details]
    • Wu, C., Kanoulas, E., de Rijke, M., & Lu, W. (2020). WN-Salience: A Corpus of News Articles with Entity Salience Annotations. In N. Calzolari, F. Béchet, P. Blache, K. Choukri, C. Cieri, T. Declerck, S. Goggi, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, & S. Piperidis (Eds.), LREC 2020: Twelfth International Conference on Language Resources and Evaluation : May 11-16, 2020, Palais du Pharo, Marseille, France : conference proceedings (pp. 2095-2102). The European Language Resources Association. https://www.aclweb.org/anthology/2020.lrec-1.257 [details]
    • Xie, X., Mao, J., Liu, Y., & de Rijke, M. (2020). Modeling User Behavior for Vertical Search: Images, Apps and Products. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 2440-2443). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401423 [details]
    • Xie, X., Mao, J., Liu, Y., de Rijke, M., Chen, H., Zhang, M., & Ma, S. (2020). Preference-based Evaluation Metrics for Web Image Search. In SIGIR '20: proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 25-30, 2020, virtual event, China (pp. 369-378). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401146 [details]
    • Zheng, J., Cai, F., Chen, H., & de Rijke, M. (2020). Pre-train, Interact, Fine-tune: A Novel Interaction Representation for Text Classification. Information Processing & Management, 57(6), Article 102215. Advance online publication. https://doi.org/10.1016/j.ipm.2020.102215 [details]

    2019

    • Azarbonyad, H., Dehghani, M., Kenter, T., Marx, M., Kamps, J., & de Rijke, M. (2019). HiTR: Hierarchical Topic Model Re-estimation for Measuring Topical Diversity of Documents. IEEE Transactions on Knowledge and Data Engineering, 31(11), 2124-2137 . Advance online publication. https://doi.org/10.1109/TKDE.2018.2874246 [details]
    • Chen, W., Cai, F., Chen, H., & de Rijke, M. (2019). A Dynamic Co-attention Network for Session-based Recommendation. In CIKM'19: Proceedings of the 28th ACM International Conference on Information & Knowledge Management : November 3-7, 2019, Beijing, China (pp. 1461-1470). Association for Computing Machinery. https://doi.org/10.1145/3357384.3357964 [details]
    • Chen, W., Cai, F., Chen, H., & de Rijke, M. (2019). Joint neural collaborative filtering for recommender systems. ACM Transactions on Information Systems, 37(4), Article 39. https://doi.org/10.1145/3343117 [details]
    • Chen, Y., Ren, P., Wang, Y., & de Rijke, M. (2019). Bayesian personalized feature interaction selection for factorization machines. In SIGIR '19: proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 21-25, 2019, Paris, France (pp. 665-674). The Association for Computing Machinery. https://doi.org/10.1145/3331184.3331196 [details]
    • Dehghani, M., Azarbonyad, H., Kamps, J., & de Rijke, M. (2019). Learning to Transform, Combine, and Reason in Open-Domain Question Answering. In K. Beuls, B. Bogaerts, G. Bontempi, P. Geurts, N. Harley, B. Lebichot, T. Lenaerts, G. Louppe, & P. Van Eecke (Eds.), Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019): Brussels, Belgium, November 6-8, 2019 Article 16 (CEUR Workshop Proceedings; Vol. 2491). CEUR-WS. http://ceur-ws.org/Vol-2491/abstract16.pdf [details]
    • Dehghani, M., Azarbonyad, H., Kamps, J., & de Rijke, M. (2019). Learning to Transform, Combine, and Reason in Open-domain Question Answering. In WSDM'19: proceedings of the Twelfth ACM International Conference on Web Search and Data Mining : February 11-15, 2019 : Melbourne, Australia (pp. 681–689). Association for Computing Machinery. https://doi.org/10.1145/3289600.3291012 [details]
    • Fang, Y., Zhao, X., Huang, P., Xiao, W., & de Rijke, M. (2019). M-HIN: Complex Embeddings for Heterogeneous Information Networks via Metagraphs. In SIGIR '19: proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 21-25, 2019, Paris, France (pp. 913–916). The Association for Computing Machinery. https://doi.org/10.1145/3331184.3331281 [details]
    • Jagerman, R., Markov, I., & de Rijke, M. (2019). When people change their mind: Off-policy evaluation in non-stationary recommendation environments. In WSDM'19: proceedings of the Twelfth ACM International Conference on Web Search and Data Mining : February 11-15, 2019 : Melbourne, Australia (pp. 447-455). Association for Computing Machinery. https://doi.org/10.1145/3289600.3290958 [details]
    • Jagerman, R., Oosterhuis, H., & de Rijke, M. (2019). To Model or to Intervene: A Comparison of Counterfactual and Online Learning to Rank from User Interactions. In SIGIR '19: proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 21-25, 2019, Paris, France (pp. 15-24). The Association for Computing Machinery. https://doi.org/10.1145/3331184.3331269 [details]
    • Jiang, B., Li, C., De Rijke, M., Yao, X., & Chen, H. (2019). Probabilistic feature selection and classification vector machine. ACM Transactions on Knowledge Discovery from Data, 13(2), Article 21. https://doi.org/10.1145/3309541 [details]
    • Jiang, S., Ren, P., Monz, C., & de Rijke, M. (2019). Improving Neural Response Diversity with Frequency-Aware Cross-Entropy Loss. In The Web Conference 2019: proceedings of the World Wide Web Conference WWW 2019 : May 13-17, 2019, San Francisco, CA, USA (pp. 2879-2885). Association for Computing Machinery. https://doi.org/10.1145/3308558.3313415 [details]
    • Li, C., & de Rijke, M. (2019). Cascading non-stationary bandits: Online learning to rank in the non-stationary cascade model. In S. Kraus (Ed.), Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence: IJCAI-19 : Macao, 10-16 August 2019 (pp. 2859-2865). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2019/396 [details]
    • Li, C., Kveton, B., Lattimore, T., Markov, I., de Rijke, M., Szepesvári, C., & Zoghi, M. (2019). BubbleRank: Safe Online Learning to Re-Rank via Implicit Click Feedback. In A. Globerson, & R. Silva (Eds.), Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence: UAI 2019, Tel Aviv, Israel, July 22-25, 2019 Article 47 AUAI Press. http://auai.org/uai2019/proceedings/papers/47.pdf [details]
    • Li, X., & de Rijke, M. (2019). Characterizing and Predicting Downloads in Academic Search. Information Processing & Management, 56(3), 394-407. Advance online publication. https://doi.org/10.1016/j.ipm.2018.10.019 [details]
    • Li, X., Chen, Y., Pettit, B., & de Rijke, M. (2019). Personalised Reranking of Paper Recommendations using Paper Content and User Behavior. ACM Transactions on Information Systems, 37(3), Article 31. Advance online publication. https://doi.org/10.1145/3312528 [details]
    • Li, Z., Kiseleva, J., & de Rijke, M. (2019). Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learning. In Thirty-Third AAAI Conference on Artificial Intelligence, Thirty-First Conference on Innovative Applications of Artificial Intelligence, The Ninth Symposium on Educational Advances in Artificial Intelligence: AAAI-19, IAAI-19, EAAI-20 : January 27-February 1, 2019, Hilton Hawaiian Village, Honolulu, Hawaii, USA (pp. 6722-6729). (Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 33). AAAI Press. https://doi.org/10.1609/aaai.v33i01.33016722 [details]
    • Li, Z., Kiseleva, J., Agarwal, A., & de Rijke, M. (2019). Learning Data-Driven Objectives to Optimize Interactive Systems. In NeurIPS LIRE 2019 Workshop: Learning with Rich Experience: Integration of Learning Paradigms NIPS. https://doi.org/10.48550/arXiv.1802.06306
    • Lin, Y., Ren, P., Chen, Z., Ren, Z., Ma, J., & de Rijke, M. (2019). Improving Outfit Recommendation with Co-supervision of Fashion Generation. In The Web Conference 2019: proceedings of the World Wide Web Conference WWW 2019 : May 13-17, 2019, San Francisco, CA, USA (pp. 1095–1105). Association for Computing Machinery. https://doi.org/10.1145/3308558.3313614 [details]
    • Lucchesee, C., Nardini, F. M., Pasumarthi, R. K., Bruch, S., Bendersky, M., Wang, X., Oosterhuis, H., Jagerman, R., & de Rijke, M. (2019). Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning. In SIGIR '19: proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 21-25, 2019, Paris, France (pp. 1419-1420). The Association for Computing Machinery. https://doi.org/10.1145/3331184.3334824 [details]
    • Ma, M., Ren, P., Lin, Y., Chen, Z., Ma, J., & de Rijke, M. (2019). π-Net: A parallel information-sharing network for shared-account cross-domain sequential recommendations. In SIGIR '19: proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 21-25, 2019, Paris, France (pp. 685-694). The Association for Computing Machinery. https://doi.org/10.1145/3331184.3331200 [details]
    • Olteanu, A., Garcia-Gathright, J., de Rijke, M., & Ekstrand, M. D. (2019). Workshop on Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval (FACTS-IR). In SIGIR '19: proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 21-25, 2019, Paris, France (pp. 1423-1425). The Association for Computing Machinery. https://doi.org/10.1145/3331184.3331644 [details]
    • Olteanu, A., Garcia-Gathright, J., de Rijke, M., & Ekstrand, M. D. (Eds.) (2019). Proceedings of FACTS-IR 2019. ArXiv. https://arxiv.org/abs/1907.05755 [details]
    • Olteanu, A., Garcia-Gathright, J., de Rijke, M., Ekstrand, M. D., Roegiest, A., Lipani, A., Beutel, A., Lucic, A., Stoica, A.-A., Das, A., Biega, A., Voorn, B., Hauff, C., Spina, D., Lewis, D., Oard, D. W., Yilmaz, E., Hasibi, F., Kazai, G., ... Kamishima, T. (2019). FACTS-IR: Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval. SIGIR Forum, 53(2), 20-43. http://sigir.org/wp-content/uploads/2019/december/p020.pdf [details]
    • Oosterhuis, H., & de Rijke, M. (2019). Optimizing Ranking Models in an Online Setting. In L. Azzopardi, B. Stein, N. Fuhr, P. Mayr, C. Hauff, & D. Hiemstra (Eds.), Advances in Information Retrieval: 41st European Conference on IR Research, ECIR 2019, Cologne, Germany, April 14-18, 2019 : proceedings (Vol. 1, pp. 382-396). (Lecture Notes in Computer Science; Vol. 11437). Springer. https://doi.org/10.1007/978-3-030-15712-8_25 [details]
    • Pei, J., Ren, P., & de Rijke, M. (2019). A Modular Task-oriented Dialogue System Using a Neural Mixture-of-Experts. In 1st Workshop on Conversational Interaction Systems (WCIS): accepted papers Article 5 WCIS. https://arxiv.org/abs/1907.05346 [details]
    • Ren, P., Chen, Z., Li, J., Ren, Z., Ma, J., & de Rijke, M. (2019). RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-based Recommendation. In Thirty-Third AAAI Conference on Artificial Intelligence, Thirty-First Conference on Innovative Applications of Artificial Intelligence, The Ninth Symposium on Educational Advances in Artificial Intelligence: AAAI-19, IAAI-19, EAAI-20 : January 27-February 1, 2019, Hilton Hawaiian Village, Honolulu, Hawaii, USA (pp. 4806-4813). (Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 33). AAAI Press. https://doi.org/10.1609/aaai.v33i01.33014806 [details]
    • Shao, T., Cai, F., Chen, H., & de Rijke, M. (2019). Length-adaptive Neural Network for Answer Selection. In SIGIR '19: proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 21-25, 2019, Paris, France (pp. 869-872). The Association for Computing Machinery. https://doi.org/10.1145/3331184.3331277 [details]
    • Vakulenko, S., Fernandez Garcia, J. D., Polleres, A., de Rijke, M., & Cochez, M. (2019). Message Passing for Complex Question Answering over Knowledge Graphs. In CIKM'19: Proceedings of the 28th ACM International Conference on Information & Knowledge Management : November 3-7, 2019, Beijing, China (pp. 1431-1440). Association for Computing Machinery. https://doi.org/10.48550/arXiv.1908.06917, https://doi.org/10.1145/3357384.3358026 [details]
    • Vakulenko, S., Revoredo, K., Di Ciccio, C., & de Rijke, M. (2019). QRFA: A Data-driven Model of Information-Seeking Dialogues. In L. Azzopardi, B. Stein, N. Fuhr, P. Mayr, C. Hauff, & D. Hiemstra (Eds.), Advances in Information Retrieval: 41st European Conference on IR Research, ECIR 2019, Cologne, Germany, April 14-18, 2019 : proceedings (Vol. 1, pp. 541-557). (Lecture Notes in Computer Science; Vol. 11437). Springer. https://doi.org/10.1007/978-3-030-15712-8_35 [details]
    • Wang, M., Ren, P., Mei, L., Chen, Z., Ma, J., & de Rijke, M. (2019). A collaborative session-based recommendation approach with parallel memory modules. In SIGIR '19: proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 21-25, 2019, Paris, France (pp. 345-354). The Association for Computing Machinery. https://doi.org/10.1145/3331184.3331210 [details]
    • Wang, S., Ren, P., Chen, Z., Ren, Z., Ma, J., & de Rijke, M. (2019). Order-free Medicine Combination Prediction with Graph Convolutional Reinforcement Learning. In CIKM'19: Proceedings of the 28th ACM International Conference on Information & Knowledge Management : November 3-7, 2019, Beijing, China (pp. 1623-1632). Association for Computing Machinery. https://doi.org/10.1145/3357384.3357965 [details]
    • Xie, X., Mao, J., Liu, Y., de Rijke, M., Ai, Q., Huang, Y., Zhang, M., & Ma, S. (2019). Improving Web Image Search with Contextual Information. In CIKM'19: Proceedings of the 28th ACM International Conference on Information & Knowledge Management : November 3-7, 2019, Beijing, China (pp. 1683-1692). Association for Computing Machinery. https://doi.org/10.1145/3357384.3358011 [details]
    • Xie, X., Mao, J., Liu, Y., de Rijke, M., Shao, Y., Ye, Z., Zhang, M., & Ma, S. (2019). Grid-based Evaluation Metrics for Web Image Search. In The Web Conference 2019: proceedings of the World Wide Web Conference WWW 2019 : May 13-17, 2019, San Francisco, CA, USA (pp. 2103–2114). Association for Computing Machinery. https://doi.org/10.1145/3308558.3313514 [details]
    • van den Akker, B., Markov, I., & de Rijke, M. (2019). ViTOR: Learning to rank webpages based on visual features. In The Web Conference 2019: proceedings of the World Wide Web Conference WWW 2019 : May 13-17, 2019, San Francisco, CA, USA (pp. 3279-3285). Association for Computing Machinery. https://doi.org/10.1145/3308558.3313419 [details]

    2018

    • Borisov, A., Kiseleva, J., Markov, I., & de Rijke, M. (2018). Calibration: A Simple Way to Improve Click Models. In CIKM'18: proceedings of the 2018 ACM International Conference on Information and Knowledge Management : October 22-26, 2018, Torino, Italy (pp. 1503-1506). The Association for Computing Machinery. https://doi.org/10.1145/3269206.3269260 [details]
    • Borisov, A., Wardenaar, M., Markov, I., & de Rijke, M. (2018). A Click Sequence Model for Web Search. In SIGIR #41 proceedings : Ann Arbor, Michigan, USA, 08-12, July 2018 (pp. 45-54). Association for Computing Machinery. https://doi.org/10.1145/3209978.3210004 [details]
    • Chen, W., Cai, F., Chen, H., & de Rijke, M. (2018). Attention-based Hierarchical Neural Query Suggestion. In SIGIR #41 proceedings: Ann Arbor, Michigan, USA, 08-12, July 2018 (pp. 1093-1096). Association for Computing Machinery. https://doi.org/10.1145/3209978.3210079 [details]
    • Chen, Y., & de Rijke, M. (2018). A Collective Variational Autoencoder for Top-N Recommendation with Side Information. In Proceedings of the 3rd Workshop on Deep Learning for Recommender Systems: In conjunction with RecSys 2018 : October 06, 2018, Vancouver, Canada (pp. 3-9). (ICPS). ACM. https://doi.org/10.1145/3270323.3270326 [details]
    • Craswell, N., Croft, W. B., de Rijke, M., Guo, J., & Mitra, B. (2018). Neural information retrieval: introduction to the special issue. Information Retrieval Journal, 21(2-3), 107-110. Advance online publication. https://doi.org/10.1007/s10791-017-9323-9 [details]
    • Feng, C., Cai, F., Chen, H., & de Rijke, M. (2018). Attentive Encoder-based Extractive Text Summarization. In CIKM'18: proceedings of the 2018 ACM International Conference on Information and Knowledge Management : October 22-26, 2018, Torino, Italy (pp. 1499-1502). The Association for Computing Machinery. https://doi.org/10.1145/3269206.3269251 [details]
    • Graus, D., Odijk, D., & de Rijke, M. (2018). The Birth of Collective Memories: Analyzing Emerging Entities in Text Streams. Journal of the Association for Information Science and Technology, 69(6), 773-786. https://doi.org/10.1002/asi.24004 [details]
    • Groth, P., Koesten, L., Mayr, P., de Rijke, M., & Simperl, E. (2018). DATA:SEARCH'18 - Searching Data on the Web: Preface. In L. Dietz, L. Koesten, & S. Verberne (Eds.), Joint Proceedings of the First International Workshop on Professional Search (ProfS2018); the Second Workshop on Knowledge Graphs and Semantics for Text Retrieval, Analysis, and Understanding (KG4IR); and the International Workshop on Data Search (DATA:SEARCH’18): co-located with (ACM SIGIR 2018) : Ann Arbor, Michigan, USA, July 12, 2018 (pp. 65-66). (CEUR Workshop Proceedings; Vol. 2127). CEUR-WS. http://ceur-ws.org/Vol-2127/preface-datasearch.pdf [details]
    • Groth, P., Koesten, L., Mayr, P., de Rijke, M., & Simperl, E. (2018). DATA:SEARCH'18 - Searching data on the web. In SIGIR #41 proceedings: Ann Arbor, Michigan, USA, 08-12, July 2018 (pp. 1419-1422). Association for Computing Machinery. https://doi.org/10.1145/3209978.3210195 [details]
    • Jagerman, R., Balog, K., & de Rijke, M. (2018). OpenSearch: Lessons Learned from an Online Evaluation Campaign. Journal of Data and Information Quality, 10(3), Article 13. Advance online publication. https://doi.org/10.1145/3239575 [details]
    • Li, C., & de Rijke, M. (2018). Incremental sparse Bayesian ordinal regression. Neural Networks, 106, 294-302. https://doi.org/10.1016/j.neunet.2018.07.015 [details]
    • Liang, S., Markov, I., Ren, Z., & de Rijke, M. (2018). Manifold Learning for Rank Aggregation. In The Web Conference 2018: companion of the World Wide Web Conference WWW2018 : April 23-27, 2018, Lyon, France (pp. 1735-1744). International World Wide Web Conferences Steering Committee. https://doi.org/10.1145/3178876.3186085 [details]
    • Onal, K. D., Zhang, Y., Altingovde, I. S., Rahman, M. M., Karagoz, P., Braylan, A., Dang, B., Chang, H.-L., Kim, H., McNamara, Q., Angert, A., Banner, E., Khetan, V., McDonnell, T., Nguyen, A. T., Xu, D., Wallace, B. C., de Rijke, M., & Lease, M. (2018). Neural Information Retrieval: at the End of the Early Years. Information Retrieval Journal, 21(2-3), 111-182. https://doi.org/10.1007/s10791-017-9321-y [details]
    • Oosterhuis, H., & de Rijke, M. (2018). Differentiable Unbiased Online Learning to Rank. In CIKM'18: proceedings of the 2018 ACM International Conference on Information and Knowledge Management : October 22-26, 2018, Torino, Italy (pp. 1293-1302). The Association for Computing Machinery. https://doi.org/10.1145/3269206.3271686 [details]
    • Oosterhuis, H., & de Rijke, M. (2018). Ranking for Relevance and Display Preferences in Complex Presentation Layouts. In SIGIR #41 proceedings: Ann Arbor, Michigan, USA, 08-12, July 2018 (pp. 845-854). Association for Computing Machinery. https://doi.org/10.1145/3209978.3209992 [details]
    • Oosterhuis, H., Culpepper, J. S., & de Rijke, M. (2018). The Potential of Learned Index Structures for Index Compression. In B. Koopman, A. Trotman, & P. Thomas (Eds.), ADCS 2018: proceedings of the 23rd Australasian Document Computing Symposium : Dunedin, New Zealand, December 11-12, 2018 Article 7 ACM. https://doi.org/10.1145/3291992.3291993 [details]
    • Pandey, G., Ren, Z., Wang, S., Veijalainen, J., & de Rijke, M. (2018). Linear Feature Extraction for Ranking. Information Retrieval Journal, 21(6), 481-506. https://doi.org/10.1007/s10791-018-9330-5 [details]
    • Ren, P., Chen, Z., Ren, Z., Wei, F., Nie, L., Ma, J., & de Rijke, M. (2018). Sentence relations for extractive summarization with deep neural networks. ACM Transactions on Information Systems, 36(4), Article 39. https://doi.org/10.1145/3200864 [details]
    • Ren, Z., He, X., Yin, D., & de Rijke, M. (2018). Information Discovery in E-commerce: Half-day SIGIR 2018 tutorial. In SIGIR #41 proceedings: Ann Arbor, Michigan, USA, 08-12, July 2018 (pp. 1379-1382). Association for Computing Machinery. https://doi.org/10.1145/3209978.3210185 [details]
    • Sepliarskaia, A., Kiseleva, J., Radlinski, F., & de Rijke, M. (2018). Preference Elicitation as an Optimization Problem. In 12th ACM Conference on Recommender Systems: October 2-7, 2018 : RECSYS : Vancouver, BC : 2018 (pp. 172-180). Association for Computing Machinery. https://doi.org/10.1145/3240323.3240352 [details]
    • Sharchilev, B., Roizner, M., Rumyantsev, A., Ozornin, D., Serdyukov, P., & de Rijke, M. (2018). Web-based Startup Success Prediction. In CIKM'18: proceedings of the 2018 ACM International Conference on Information and Knowledge Management : October 22-26, 2018, Torino, Italy (pp. 2283-2291). The Association for Computing Machinery. https://doi.org/10.1145/3269206.3272011 [details]
    • Sharchilev, B., Ustinovsky, Y., Serdyukov, P., & de Rijke, M. (2018). Finding Influential Training Samples for Gradient Boosted Decision Trees. Proceedings of Machine Learning Research, 80, 4577-4585. http://proceedings.mlr.press/v80/sharchilev18a.html [details]
    • Vakulenko, S., de Rijke, M., Cochez, M., Savenkov, V., & Polleres, A. (2018). Measuring Semantic Coherence of a Conversation. In D. Vrandečić, K. Bontcheva, M. C. Suárez-Figueroa, V. Presutti, I. Celino, M. Sabou, L.-A. Kaffee, & E. Simperl (Eds.), The Semantic Web – ISWC 2018: 17th International Semantic Web Conference, Monterey, CA, USA, October 8–12, 2018 : proceedings (Vol. I, pp. 634-651). (Lecture Notes in Computer Science; Vol. 11136). Springer. https://doi.org/10.1007/978-3-030-00671-6_37 [details]
    • Van Gysel, C., & de Rijke, M. (2018). Pytrec_eval: An Extremely Fast Python Interface to TREC_eval. In SIGIR #41 proceedings: Ann Arbor, Michigan, USA, 08-12, July 2018 (pp. 873-876). Association for Computing Machinery. https://doi.org/10.1145/3209978.3210065 [details]
    • Van Gysel, C., de Rijke, M., & Kanoulas, E. (2018). Mix 'n Match: Integrating Text Matching and Product Substitutability within Product Search. In CIKM '18: proceedings of the 2018 ACM International Conference on Information and Knowledge Management : October 22-26, 2018, Torino, Italy (pp. 1373-1382). The Association for Computing Machinery. https://doi.org/10.1145/3269206.3271668 [details]
    • Van Gysel, C., de Rijke, M., & Kanoulas, E. (2018). Neural vector spaces for unsupervised information retrieval. ACM Transactions on Information Systems, 36(4), Article 38. https://doi.org/10.1145/3196826 [details]
    • Voskarides, N., Meij, E., Reinanda, R., Khaitan, A., Osborne, M., Stefanoni, G., Kambadur, P., & de Rijke, M. (2018). Weakly-supervised contextualization of knowledge graph facts. In SIGIR #41 proceedings : Ann Arbor, Michigan, USA, 08-12, July 2018 (pp. 765-774). Association for Computing Machinery. https://doi.org/10.1145/3209978.3210031 [details]
    • Xie, X., Liu, Y., de Rijke, M., He, J., Zhang, M., & Ma, S. (2018). Why people search for images using web search engines. In WSDM'18: proceedings of the Eleventh ACM International Conference on Web Search and Data Mining : February 5-9, 2018, Marina Del Rey, CA, USA (pp. 655-663). Association for Computing Machinery. https://doi.org/10.1145/3159652.3159686 [details]
    • Xie, X., Mao, J., de Rijke, M., Zhang, R., Zhang, M., & Ma, S. (2018). Constructing an Interaction Behavior Model for Web Image Search. In SIGIR #41 proceedings: Ann Arbor, Michigan, USA, 08-12, July 2018 (pp. 425-434). Association for Computing Machinery. https://doi.org/10.1145/3209978.3209990 [details]
    • de Rijke, M. (2018). Learning to Search for Datasets. In The Web Conference 2018: companion of the World Wide Web Conference WWW2018 : April 23-27, 2018, Lyon, France (pp. 1483). International World Wide Web Conferences Steering Committee. https://doi.org/10.1145/3184558.3191604 [details]

    2017

    • Azarbonyad, H., Dehghani, M., Kenter, T., Marx, M., Kamps, J., & de Rijke, M. (2017). Hierarchical Re-estimation of Topic Models for Measuring Topical Diversity. In J. M. Jose, C. Hauff, I. S. Altıngovde, D. Song, D. Albakour, S. Watt, & J. Tait (Eds.), Advances in Information Retrieval: 39th European Conference on IR Research, ECIR 2017, Aberdeen, UK, April 8–13, 2017 : proceedings (pp. 68-81). (Lecture Notes in Computer Science; Vol. 10193). Springer. https://doi.org/10.1007/978-3-319-56608-5_6 [details]
    • Chen, Y., Zhao, X., & de Rijke, M. (2017). Top-N Recommendation with High-dimensional Side Information via Locality Preserving Projection. In SIGIR'17 : proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval: August 7-11, 2017, Shinjuku, Tokyo, Japan (pp. 985-988). Association for Computing Machinery. https://doi.org/10.1145/3077136.3080697 [details]
    • Degenhardt, J., Kallumadi, S., de Rijke, M., Si, L., Trotman, A., & Xu, Y. (2017). SIGIR 2017 Workshop on eCommerce (ECOM17). In SIGIR'17 : proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval: August 7-11, 2017, Shinjuku, Tokyo, Japan (pp. 1425-1426). Association for Computing Machinery. https://doi.org/10.1145/3077136.3084367 [details]
    • Dehghani, M., Azarbonyad, H., Kamps, J., & de Rijke, M. (2017). Share your Model instead of your Data: Privacy Preserving Mimic Learning for Ranking. In Neu-IR: Workshop on Neural Information Retrieval: accepted papers ArXiv. https://arxiv.org/abs/1707.07605 [details]
    • Jagerman, R., Eickhoff, C., & de Rijke, M. (2017). Computing Web-scale Topic Models using an Asynchronous Parameter Server. In SIGIR'17 : proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval: August 7-11, 2017, Shinjuku, Tokyo, Japan (pp. 1337-1340). Association for Computing Machinery. https://doi.org/10.1145/3077136.3084135 [details]
    • Jagerman, R., Kiseleva, J., & de Rijke, M. (2017). Modeling Label Ambiguity for List-Wise Neural Learning to Rank. In Neu-IR: Workshop on Neural Information Retrieval: accepted papers ArXiv. https://arxiv.org/abs/1707.07493 [details]
    • Jagerman, R., Oosterhuis, H., & de Rijke, M. (2017). Query-level Ranker Specialization. In N. Ferro, C. Lucchese, M. Maistro, & R. Perego (Eds.), Proceedings of the 1st International Workshop on LEARning Next gEneration Rankers: co-located with the 3rd ACM International Conference on the Theory of Information Retrieval (ICTIR 2017) : Amsterdam, The Netherlands, October 1, 2017 (CEUR Workshop Proceedings; Vol. 2007). CEUR-WS. http://ceur-ws.org/Vol-2007/LEARNER2017_full_2.pdf [details]
    • Kenter, T., Borisov, A., Van Gysel, C., Dehghani, M., de Rijke, M., & Mitra, B. (2017). Neural Networks for Information Retrieval. In SIGIR'17 : proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval: August 7-11, 2017, Shinjuku, Tokyo, Japan (pp. 1403-1406). Association for Computing Machinery. https://doi.org/10.1145/3077136.3082062 [details]
    • Li, X., & de Rijke, M. (2017). Academic search in response to major scientific events. In P. Mayr, I. Frommholz, & G. Cabanac (Eds.), Proceedings of the Fifth Workshop on Bibliometric-enhanced Information Retrieval (BIR): co-located with the 39th European Conference on Information Retrieval (ECIR 2017) : Aberdeen, UK, April 9th, 2017 (pp. 41-50). (CEUR Workshop Proceedings; Vol. 1823). CEUR-WS. http://ceur-ws.org/Vol-1823/paper4.pdf [details]
    • Li, X., & de Rijke, M. (2017). Do topic shift and query reformulation patterns correlate in academic search? In J. M. Jose, C. Hauff, I. S. Altıngovde, D. Song, D. Albakour, S. Watt, & J. Tait (Eds.), Advances in Information Retrieval: 39th European Conference on IR Research, ECIR 2017, Aberdeen, UK, April 8–13, 2017 : proceedings (pp. 146-159). (Lecture Notes in Computer Science; Vol. 10193). Springer. https://doi.org/10.1007/978-3-319-56608-5_12 [details]
    • Li, X., Schijvenaars, B. J. A., & de Rijke, M. (2017). Investigating queries and search failures in academic search. Information Processing and Management, 53(3), 666-683. Advance online publication. https://doi.org/10.1016/j.ipm.2017.01.005 [details]
    • Li, Z., & de Rijke, M. (2017). The impact of linkage methods in hierarchical clustering for active learning to rank. In SIGIR'17 : proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval: August 7-11, 2017, Shinjuku, Tokyo, Japan (pp. 941-944). Association for Computing Machinery. https://doi.org/10.1145/3077136.3080684 [details]
    • Li, Z., Kiseleva, J., de Rijke, M., & Grotov, A. (2017). Towards learning reward functions from user interactions. In ICTIR'17: proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval: October 1-4, 2017, Amsterdam, the Netherlands (pp. 289-292). Association for Computing Machinery. https://doi.org/10.1145/3121050.3121098 [details]
    • Malkevich, S., Markov, I., Michailova, E., & de Rijke, M. (2017). Evaluating and Analyzing Click Simulation in Web Search. In ICTIR'17: proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval: October 1-4, 2017, Amsterdam, the Netherlands (pp. 281-284). Association for Computing Machinery. https://doi.org/10.1145/3121050.3121096 [details]
    • Markov, I., Borisov, A., & de Rijke, M. (2017). Online Expectation-Maximization for Click Models. In CIKM'17 : proceedings of the 2017 ACM on Conference on Information and Knowledge Management: November 6-10, 2017, Singapore, Singapore (pp. 2195-2198). Association for Computing Machinery. https://doi.org/10.1145/3132847.3133053 [details]
    • Oosterhuis, H., & de Rijke, M. (2017). Balancing Speed and Quality in Online Learning to Rank for Information Retrieval. In CIKM'17 : proceedings of the 2017 ACM on Conference on Information and Knowledge Management: November 6-10, 2017, Singapore, Singapore (pp. 277-286). Association for Computing Machinery. https://doi.org/10.1145/3132847.3132896 [details]
    • Oosterhuis, H., & de Rijke, M. (2017). Sensitive and Scalable Online Evaluation with Theoretical Guarantees. In CIKM'17 : proceedings of the 2017 ACM on Conference on Information and Knowledge Management: November 6-10, 2017, Singapore, Singapore (pp. 77-86). Association for Computing Machinery. https://doi.org/10.1145/3132847.3132895 [details]
    • Ren, P., Chen, Z., Ren, Z., Wei, F., Ma, J., & de Rijke, M. (2017). Leveraging contextual sentence relations for extractive summarization using a neural attention model. In SIGIR'17 : proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval: August 7-11, 2017, Shinjuku, Tokyo, Japan (pp. 95-104). Association for Computing Machinery. https://doi.org/10.1145/3077136.3080792 [details]
    • Van Gysel, C., Kanoulas, E., & de Rijke, M. (2017). Pyndri: a Python Interface to the Indri Search Engine. In J. M. Jose, C. Hauff, I. S. Altıngovde, D. Song, D. Albakour, S. Watt, & J. Tait (Eds.), Advances in Information Retrieval: 39th European Conference on IR Research, ECIR 2017, Aberdeen, UK, April 8–13, 2017 : proceedings (pp. 744-748). (Lecture Notes in Computer Science; Vol. 10193). Springer. https://doi.org/10.1007/978-3-319-56608-5_74 [details]
    • Van Gysel, C., de Rijke, M., & Kanoulas, E. (2017). Semantic Entity Retrieval Toolkit. In Neu-IR: Workshop on Neural Information Retrieval: accepted papers ArXiv. https://arxiv.org/abs/1706.03757 [details]
    • Van Gysel, C., de Rijke, M., & Kanoulas, E. (2017). Structural Regularities in Text-based Entity Vector Spaces. In ICTIR'17: proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval: October 1-4, 2017, Amsterdam, the Netherlands (pp. 3-10). Association for Computing Machinery. https://doi.org/10.1145/3121050.3121066 [details]
    • Voskarides, N., Meij, E., & de Rijke, M. (2017). Generating descriptions of entity relationships. In J. M. Jose, C. Hauff, I. S. Altıngovde, D. Song, D. Albakour, S. Watt, & J. Tait (Eds.), Advances in Information Retrieval: 39th European Conference on IR Research, ECIR 2017, Aberdeen, UK, April 8–13, 2017 : proceedings (pp. 317-330). (Lecture Notes in Computer Science; Vol. 10193). Springer. https://doi.org/10.1007/978-3-319-56608-5_25 [details]

    2016

    • Borisov, A., Markov, I., de Rijke, M., & Serdyukov, P. (2016). A context-aware time model for web search. In SIGIR'16: the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval: Pisa, Italy , July 17-21, 2016 (pp. 205-214). Association for Computing Machinery. https://doi.org/10.1145/2911451.2911504 [details]
    • Borisov, A., Markov, I., de Rijke, M., & Serdyukov, P. (2016). A neural click model for web search. In WWW'16: proceedings of the 25th International Conference on World Wide Web : May 11-15, 2016, Montreal, Canada (pp. 531-541). Association for Computing Machinery. https://doi.org/10.1145/2872427.2883033 [details]
    • Borisov, A., Serdyukov, P., & de Rijke, M. (2016). Using metafeatures to increase the effectiveness of latent semantic models in web search. In WWW'16: proceedings of the 25th International Conference on World Wide Web : May 11-15, 2016, Montreal, Canada (pp. 1081-1091). Association for Computing Machinery. https://doi.org/10.1145/2872427.2882987 [details]
    • Bron, M., Van Gorp, J., & de Rijke, M. (2016). Media studies research in the data-driven age: How research questions evolve. Journal of the Association for Information Science and Technology, 67(7), 1535-1554. Advance online publication. https://doi.org/10.1002/asi.23458 [details]
    • Cai, F., & de Rijke, M. (2016). A Survey of Query Auto Completion in Information Retrieval. Foundations and Trends in Information Retrieval, 10(4), 1-92. https://doi.org/10.1561/1500000055 [details]
    • Cai, F., & de Rijke, M. (2016). Selectively personalizing query auto-completion. In SIGIR'16: the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval: Pisa, Italy , July 17-21, 2016 (pp. 993-996). Association for Computing Machinery. https://doi.org/10.1145/2911451.2914686 [details]
    • Cai, F., Liang, S., & de Rijke, M. (2016). Prefix-adaptive and time-sensitive personalized query auto completion. IEEE Transactions on Knowledge and Data Engineering, 28(9), 2452-2466. https://doi.org/10.1109/TKDE.2016.2568179 [details]
    • Chuklin, A., & de Rijke, M. (2016). Incorporating clicks, attention and satisfaction into a search engine result page evaluation model. In CIKM'16: proceedings of the 2016 ACM Conference on Information and Knowledge Management : October 24-28, 2016, Indianapolis, IN, USA (pp. 175-184). Association for Computing Machinery. https://doi.org/10.1145/2983323.2983829 [details]
    • Chuklin, A., Markov, I., & de Rijke, M. (2016). Click models for web search and their applications to IR: WSDM 2016 Tutorial. In WSDM'16: proceedings of the Ninth ACM International Conference on Web Search and Data Mining : February 22-25, 2016, San Francisco, CA, USA (pp. 689-690). Association for Computing Machinery. https://doi.org/10.1145/2835776.2855113 [details]
    • Craswell, N., Croft, W. B., Guo, J., Mitra, B., & de Rijke, M. (2016). Neu-IR: The SIGIR 2016 Workshop on Neural Information Retrieval. In SIGIR'16: the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval: Pisa, Italy , July 17-21, 2016 (pp. 1245-1246). Association for Computing Machinery. https://doi.org/10.1145/2911451.2917762 [details]
    • Graus, D., Tsagkias, M., Weerkamp, W., Meij, E., & de Rijke, M. (2016). Dynamic collective entity representations for entity ranking. In WSDM'16 : proceedings of the Ninth ACM International Conference on Web Search and Data Mining : February 22-25, 2016, San Francisco, CA, USA (pp. 595-604). Association for Computing Machinery. https://doi.org/10.1145/2835776.2835819 [details]
    • Grotov, A., & de Rijke, M. (2016). Online learning to rank for information retrieval: SIGIR 2016 tutorial. In SIGIR'16: the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval: Pisa, Italy , July 17-21, 2016 (pp. 1215-1218). Association for Computing Machinery. https://doi.org/10.1145/2911451.2914798 [details]
    • Kenter, T., Borisov, A., & de Rijke, M. (2016). Siamese CBOW: Optimizing word embeddings for sentence representations. In K. Erk, & N. A. Smith (Eds.), The 54th Annual Meeting of the Association for Computational Linguistics : ACL 2016: proceedings of the conference : August 7-12, 2016, Berlin Germany (Vol. 1, pp. 941-951). Association for Computational Linguistics. https://doi.org/10.18653/v1/P16-1089 [details]
    • Liang, S., & de Rijke, M. (2016). Formal language models for finding groups of experts. Information Processing & Management, 52(4), 529-549. Advance online publication. https://doi.org/10.1016/j.ipm.2015.11.005 [details]
    • Oosterhuis, H., Schuth, A., & de Rijke, M. (2016). Probabilistic Multileave Gradient Descent. In N. Ferro, F. Crestani, M-F. Moens, J. Mothe, F. Silvestri, G. M. Di Nunzio, C. Hauff, & G. Silvello (Eds.), Advances in Information Retrieval: 38th European Conference on IR Research, ECIR 2016, Padua, Italy, March 20-23, 2016 : proceedings (pp. 661-668). (Lecture Notes in Computer Science; Vol. 9626). Springer. https://doi.org/10.1007/978-3-319-30671-1_50 [details]
    • Peetz, M-H., de Rijke, M., & Kaptein, R. (2016). Estimating reputation polarity on microblog posts. Information Processing & Management, 52(2), 193-216. Advance online publication. https://doi.org/10.1016/j.ipm.2015.07.003 [details]
    • Reinanda, R., Meij, E., & de Rijke, M. (2016). Document filtering for long-tail entities. In CIKM'16: proceedings of the 2016 ACM Conference on Information and Knowledge Management : October 24-28, 2016, Indianapolis, IN, USA (pp. 771-780). Association for Computing Machinery. https://doi.org/10.1145/2983323.2983728 [details]
    • Ren, Z., Inel, O., Aroyo, L., & de Rijke, M. (2016). Time-aware multi-viewpoint summarization of multilingual social text streams. In CIKM'16: proceedings of the 2016 ACM Conference on Information and Knowledge Management : October 24-28, 2016, Indianapolis, IN, USA (pp. 387-396). Association for Computing Machinery. https://doi.org/10.1145/2983323.2983710 [details]
    • Ren, Z., Song, H., Li, P., Liang, S., Ma, J., & de Rijke, M. (2016). Using Sparse Coding for Answer Summarization in Non-Factoid Community Question-Answering. In Second WebQA workshop. Accepted papers University of Waterloo. http://plg2.cs.uwaterloo.ca/~avtyurin/WebQA2016/ [details]
    • Sauer, S., & de Rijke, M. (2016). Seeking Serendipity: A Living Lab Approach to Understanding Creative Retrieval in Broadcast Media Production. In SIGIR'16: the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval: Pisa, Italy , July 17-21, 2016 (pp. 989-992). Association for Computing Machinery. https://doi.org/10.1145/2911451.2914721 [details]
    • Schuth, A., Oosterhuis, H., Whiteson, S., & de Rijke, M. (2016). Multileave Gradient Descent for Fast Online Learning to Rank. In WSDM'16 : proceedings of the Ninth ACM International Conference on Web Search and Data Mining : February 22-25, 2016, San Francisco, CA, USA (pp. 457-466). Association for Computing Machinery. https://doi.org/10.1145/2835776.2835804 [details]
    • Van Gysel, C., Kanoulas, E., & de Rijke, M. (2016). Lexical query modeling in session search. In ICTIR'16: proceedings of the 2016 ACM International Conference on the Theory of Information Retrieval : September 12-16, 2016, Newark, Delaware, USA (pp. 69-72). The Association for Computing Machinery. https://doi.org/10.1145/2970398.2970422 [details]
    • Van Gysel, C., de Rijke, M., & Kanoulas, E. (2016). Learning Latent Vector Spaces for Product Search. In CIKM'16: proceedings of the 2016 ACM Conference on Information and Knowledge Management : October 24-28, 2016, Indianapolis, IN, USA (pp. 165-174). Association for Computing Machinery. https://doi.org/10.1145/2983323.2983702 [details]
    • Van Gysel, C., de Rijke, M., & Worring, M. (2016). Unsupervised, Efficient and Semantic Expertise Retrieval. In WWW'16: proceedings of the 25th International Conference on World Wide Web : May 11-15, 2016, Montreal, Canada (pp. 1069-1079). Association for Computing Machinery. https://doi.org/10.1145/2872427.2882974 [details]
    • Zhao, Y., Liang, S., Ren, Z., Ma, J., Yilmaz, E., & de Rijke, M. (2016). Explainable user clustering in short text streams. In SIGIR'16: the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval: Pisa, Italy , July 17-21, 2016 (pp. 155-164). Association for Computing Machinery. https://doi.org/10.1145/2911451.2911522 [details]
    • van Doorn, J., Odijk, D., Roijers, D. M., & de Rijke, M. (2016). Balancing relevance criteria through multi-objective optimization. In SIGIR'16: the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval: Pisa, Italy , July 17-21, 2016 (pp. 769-772). Association for Computing Machinery. https://doi.org/10.1145/2911451.2914708 [details]

    2015

    • Buitinck, L., van Amerongen, J., Tan, E., & de Rijke, M. (2015). Multi-emotion detection in user-generated reviews. In A. Hanbury, G. Kazai, A. Rauber, & N. Fuhr (Eds.), Advances in Information Retrieval: 37th European Conference on IR Research, ECIR 2015, Vienna, Austria, March 29-April 2, 2015 : proceedings (pp. 43-48). (Lecture Notes in Computer Science ; Vol. 9022). Springer. https://doi.org/10.1007/978-3-319-16354-3_5 [details]
    • Chuklin, A., & de Rijke, M. (2015). Deriving vertical orientation from anchor-based assessments. In K. Zhou, R. J. Luo, D. Hiemstra, & J. Jose (Eds.), Proceedings of the First International Workshop on Heterogeneous Information Access (HIA 2015): February 6, 2015, Shanghai, China (pp. 7-9). WSDM 2015. https://sites.google.com/site/hiaworkshop/hia15/accepted-papers [details]
    • Chuklin, A., Markov, I., & de Rijke, M. (2015). Click Models for Web Search. (Synthesis Lectures on Information Concepts, Retrieval, and Services; Vol. 43). Morgan & Claypool. https://doi.org/10.2200/S00654ED1V01Y201507ICR043 [details]
    • Chuklin, A., Schuth, A., Zhou, K., & de Rijke, M. (2015). A comparative analysis of interleaving methods for aggregated search. ACM Transactions on Information Systems, 33(2), Article 5. https://doi.org/10.1145/2668120 [details]
    • Grotov, A., Chuklin, A., Markov, I., Stout, L., Xumara, F., & de Rijke, M. (2015). A comparative study of click models for web search. In J. Mothe, J. Savoy, J. Kamps, K. Pinel-Sauvagnat, G. J. F. Jones, E. SanJuan, L. Cappellato, & N. Ferro (Eds.), Experimental IR Meets Multilinguality, Multimodality, and Interaction: 6th International Conference of the CLEF Association, CLEF'15, Toulouse, France, September 8–11, 2015 : proceedings (pp. 78-90). (Lecture Notes in Computer Science; Vol. 9283). Springer. https://doi.org/10.1007/978-3-319-24027-5_7 [details]
    • Gârbacea, C., Odijk, D., Graus, D. P., Sijaranamual, I., & de Rijke, M. (2015). Combining multiple signals for semanticizing tweets: University of Amsterdam at #Microposts2015. In R. Rowe, M. Stankovic, & A-S. Dadzie (Eds.), Proceedings of the the 5th Workshop on Making Sense of Microposts: co-located with the 24th International World Wide Web Conference (WWW 2015) : Florence, Italy, May 18th, 2015 (pp. 59-60). (CEUR Workshop Proceedings; Vol. 1395). CEUR-WS. http://ceur-ws.org/Vol-1395/paper_17.pdf [details]
    • Kenter, T., & de Rijke, M. (2015). Short Text Similarity with Word Embeddings. In CIKM'15: proceedings of the 24th ACM International Conference on Information and Knowledge Management : October 19-23, 2015, Melbourne, Australia (pp. 1411-1420). The Association for Computing Machinery. https://doi.org/10.1145/2806416.2806475 [details]
    • Kenter, T., Balog, K., & de Rijke, M. (2015). Evaluating document filtering systems over time. Information Processing & Management, 51(6), 791-808. Advance online publication. https://doi.org/10.1016/j.ipm.2015.03.005 [details]
    • Kenter, T., Wevers, M., Huijnen, P., & de Rijke, M. (2015). Ad Hoc Monitoring of Vocabulary Shifts over Time. In CIKM'15: proceedings of the 24th ACM International Conference on Information and Knowledge Management : October 19-23, 2015, Melbourne, Australia (pp. 1191-1200 ). The Association for Computing Machinery. https://doi.org/10.1145/2806416.2806474 [details]
    • Li, X., Tang, J., Wang, T., Luo, Z., & de Rijke, M. (2015). Automatically assessing Wikipedia article quality by exploiting article-editor networks. In A. Hanbury, G. Kazai, A. Rauber, & N. Fuhr (Eds.), Advances in Information Retrieval: 37th European Conference on IR Research, ECIR 2015, Vienna, Austria, March 29-April 2, 2015 : proceedings (pp. 574-580). (Lecture Notes in Computer Science ; Vol. 9022). Springer. https://doi.org/10.1007/978-3-319-16354-3_64 [details]
    • Liang, S., & de Rijke, M. (2015). Burst-aware data fusion for microblog search. Information Processing & Management, 51(2), 89-113. https://doi.org/10.1016/j.ipm.2014.10.008 [details]
    • Norouzzadeh Ravari, Y., Markov, I., Grotov, A., Clements, M., & de Rijke, M. (2015). User behavior in location search on mobile devices. In A. Hanbury, G. Kazai, A. Rauber, & N. Fuhr (Eds.), Advances in Information Retrieval: 37th European Conference on IR Research, ECIR 2015, Vienna, Austria, March 29-April 2, 2015 : proceedings (pp. 728-733). (Lecture Notes in Computer Science ; Vol. 9022). Springer. https://doi.org/10.1007/978-3-319-16354-3_79 [details]
    • Odijk, D., Meij, E., Sijaranamual, I., & de Rijke, M. (2015). Dynamic Query Modeling for Related Content Finding. In SIGIR 2015: proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval: August 9-13, 2015, Santiago, Chile (pp. 43-52). Association for Computing Machinery. https://doi.org/10.1145/2766462.2767715 [details]
    • Reinanda, R., Meij, E., & de Rijke, M. (2015). Mining, ranking and recommending entity aspects. In SIGIR 2015: proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval: August 9-13, 2015, Santiago, Chile (pp. 263-272). Association for Computing Machinery. https://doi.org/10.1145/2766462.2767724 [details]
    • Schuth, A., Bruintjes, R-J., Büttner, F., van Doorn, J., Groenland, C., Oosterhuis, H., Tran, C-N., Veeling, B., van der Velde, J., Wechsler, R., Woudenberg, D., & de Rijke, M. (2015). Probabilistic Multileave for Online Retrieval Evaluation. In SIGIR 2015: proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval: August 9-13, 2015, Santiago, Chile (pp. 955-958). Association for Computing Machinery. https://doi.org/10.1145/2766462.2767838 [details]
    • Van Gysel, C., Goethals, B., & de Rijke, M. (2015). Determining the Presence of Political Parties in Social Circles. In Proceedings of the Ninth International Conference on Web and Social Media: ICWSM 2015: University of Oxford, Oxford, UK, May 26-29, 2015 (pp. 690-693). AAAI Press. http://www.aaai.org/ocs/index.php/ICWSM/ICWSM15/paper/view/10531 [details]
    • Voskarides, N., Meij, E., Tsagkias, M., de Rijke, M., & Weerkamp, W. (2015). Learning to Explain Entity Relationships in Knowledge Graphs. In C. Zong, & M. Strube (Eds.), ACL-IJCNLP 2015: The 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing : proceedings of the conference : ACL 2015, July 26-31, Beijing, China (Vol. 1, pp. 564-574). Association for Computational Linguistics. http://www.aclweb.org/anthology/P15-1055 [details]
    • Zoghi, M., Whiteson, S., & de Rijke, M. (2015). MergeRUCB: A method for large-scale online ranker evaluation. In WSDM'15: proceedings of the Eighth ACM International Conference on Web Search and Data Mining: Jan. 31-Feb. 6, 2015, Shanghai, China (pp. 17-26). Association for Computing Machinery. https://doi.org/10.1145/2684822.2685290 [details]
    • van Dijk, D., Tsagkias, M., & de Rijke, M. (2015). Early detection of topical expertise in community question and answering. In SIGIR 2015: proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval: August 9-13, 2015, Santiago, Chile (pp. 995-998). Association for Computing Machinery. https://doi.org/10.1145/2766462.2767840 [details]

    2014

    • Amigó, E., Carrillo-de-Albornoz, J., Chugur, I., Corujo, A., Gonzalo, J., Meij, E., de Rijke, M., & Spina, D. (2014). Overview of RepLab 2014: Author Profiling and Reputation Dimensions for Online Reputation Management. In E. Kanoulas, M. Lupu, P. Clough, M. Sanderson, M. Hall, A. Hanbury, & E. Toms (Eds.), Information Access Evaluation : Multilinguality, Multimodality, and Interaction: 5th International Conference of the CLEF Initiative, CLEF 2014, Sheffield, UK, September 15-18, 2014 : proceedings (pp. 307-322). (Lecture Notes in Computer Science; Vol. 8685). Springer. https://doi.org/10.1007/978-3-319-11382-1_24 [details]
    • Bron, M., Wang, S., van der Werf, T., & de Rijke, M. (2014). A Social Bookmarking System to Support Cluster Driven Archival Arrangement. In IIiX2014, building bridges: behaviour, systems, interfaces : Regensburg, 26.-30. August 2014 : proceedings of the 5th Information Interaction in Context Symposium (pp. 295-298). ACM. https://doi.org/10.1145/2637002.2637046 [details]
    • Burscher, B., Odijk, D., Vliegenthart, R., de Rijke, M., & de Vreese, C. H. (2014). Teaching the computer to code frames in news: comparing two supervised machine learning approaches to frame analysis. Communication Methods and Measures, 8(3), 190-206. https://doi.org/10.1080/19312458.2014.937527 [details]
    • Cai, F., Liang, S., & de Rijke, M. (2014). Personalized document re-ranking based on Bayesian probabilistic matrix factorization. In SIGIR '14: proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval: July 6-11 2014, Gold Coast, Queensland, Australia (pp. 835-838). ACM. https://doi.org/10.1145/2600428.2609453 [details]
    • Cai, F., Liang, S., & de Rijke, M. (2014). Time-sensitive personalized query auto-completion. In J. Li, & X. S. Wang (Eds.), CIKM '14: proceedings of the 2014 ACM International Conference on Information and Knowledge Management: November 3-7, 2014, Shanghai, China (pp. 1599-1608). Association for Computing Machinery. https://doi.org/10.1145/2661829.2661921 [details]
    • Chuklin, A., Zhou, K., Schuth, A., Sietsma, F., & de Rijke, M. (2014). Evaluating intuitiveness of vertical-aware click models. In SIGIR '14: proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval: July 6-11 2014, Gold Coast, Queensland, Australia (pp. 1075-1078). ACM. https://doi.org/10.1145/2600428.2609513 [details]
    • Graus, D., Peetz, M-H., Odijk, D., de Rooij, O., & de Rijke, M. (2014). yourHistory - Semantic linking for a personalized timeline of historic events. In M. d'Aquin, S. Dietze, H. Drachsler, M. Guy, & E. Herder (Eds.), Proceedings of the LinkedUp Veni Competition on Linked and Open Data for Education: held at the Open Knowledge Conference (OKCon 2013) : Geneva, Switzerland, September 17, 2013 Article 6 (CEUR Workshop Proceedings; Vol. 1124). CEUR-WS. http://ceur-ws.org/Vol-1124/linkedup_veni2013_07.pdf [details]
    • Graus, D., Tsagkias, M., Buitinck, L., & de Rijke, M. (2014). Generating Pseudo-ground Truth for Predicting New Concepts in Social Streams. In M. de Rijke, T. Kenter, A. P. de Vries, C. X. Zhai, F. de Jong, K. Radinsky, & K. Hofmann (Eds.), Advances in Information Retrieval: 36th European Conference on IR Research, ECIR 2014, Amsterdam, The Netherlands, April 13-16, 2014: proceedings (pp. 286-298). (Lecture Notes in Computer Science). Springer. https://doi.org/10.1007/978-3-319-06028-6_24 [details]
    • Graus, D., van Dijk, D., Tsagkias, M., Weerkamp, W., & de Rijke, M. (2014). Recipient Recommendation in Enterprises Using Communication Graphs and Email Content. In SIGIR '14: proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval: July 6-11 2014, Gold Coast, Queensland, Australia (pp. 1079-1082). ACM. https://doi.org/10.1145/2600428.2609514 [details]
    • Gârbacea, C., Tsagkias, M., & de Rijke, M. (2014). Detecting the reputation polarity of microblog posts. In T. Schaub, G. Friedrich, & B. O'Sullivan (Eds.), ECAI 2014: 21st European Conference on Artificial Intelligence, 18-22 August 2014, Prague, Czech Republic: including Prestigious Applications of Intelligent Systems (PAIS 2014): proceedings (pp. 339-334). (Frontiers in Artificial Intelligence and Applications; Vol. 263). IOS Press. https://doi.org/10.3233/978-1-61499-419-0-339 [details]
    • Gârbacea, C., Tsagkias, M., & de Rijke, M. (2014). Feature selection and data sampling methods for learning reputation dimensions: The University of Amsterdam at RepLab 2014. In L. Cappellato, N. Ferro, M. Halvey, & W. Kraaij (Eds.), Working Notes for CLEF 2014 Conference: Sheffield, UK, September 15-18, 2014 (pp. 1479-1490). (CEUR Workshop Proceedings; Vol. 1180). CEUR-WS. http://ceur-ws.org/Vol-1180/CLEF2014wn-Rep-GarbaceaEt2014.pdf [details]
    • Hofmann, K., Schuth, A., Bellogín, A., & de Rijke, M. (2014). Effects of position bias on click-based recommender evaluation. In M. de Rijke, T. Kenter, A. P. de Vries, C. X. Zhai, F. de Jong, K. Radinsky, & K. Hofmann (Eds.), Advances in Information Retrieval: 36th European Conference on IR Research, ECIR 2014, Amsterdam, The Netherlands, April 13-16, 2014: proceedings (pp. 624-630). (Lecture Notes in Computer Science). Springer. https://doi.org/10.1007/978-3-319-06028-6_67 [details]
    • Hofmann, K., Whiteson, S., Schuth, A., & de Rijke, M. (2014). Learning to Rank for Information Retrieval from User Interactions. ACM SIGWEB Newsletter, 2014(Spring), Article 5. https://doi.org/10.1145/2591453.2591458 [details]
    • Huijnen, P., Laan, F., de Rijke, M., & Pieters, T. (2014). A digital humanities approach to the history of science: eugenics revisited in hidden debates by means of semantic text mining. In A. Nadamoto, A. Jatowt, A. Wierzbicki, & J. L. Leidner (Eds.), Social Informatics: SocInfo 2013 International Workshops QMC and HISTOINFORMATICS: Kyoto, Japan, November 25, 2013: revised selected papers (pp. 71-85). (Lecture Notes in Computer Science; Vol. 8359). Springer. https://doi.org/10.1007/978-3-642-55285-4_6 [details]
    • Lefortier, D., Serdyukov, P., & de Rijke, M. (2014). Online exploration for detecting shifts in fresh intent. In J. Li, & X. S. Wang (Eds.), CIKM '14: proceedings of the 2014 ACM International Conference on Information and Knowledge Management: November 3-7, 2014, Shanghai, China (pp. 589-598). Association for Computing Machinery. https://doi.org/10.1145/2661829.2661947 [details]
    • Lefortier, D., Serdyukov, P., Romanenko, F., & de Rijke, M. (2014). Blending vertical and web results: A case study using video intent. In M. de Rijke, T. Kenter, A. P. de Vries, C. X. Zhai, F. de Jong, K. Radinsky, & K. Hofmann (Eds.), Advances in Information Retrieval: 36th European Conference on IR Research, ECIR 2014, Amsterdam, The Netherlands, April 13-16, 2014: proceedings (pp. 184-196). (Lecture Notes in Computer Science). Springer. https://doi.org/10.1007/978-3-319-06028-6_16 [details]
    • Liang, S., Ren, Z., & de Rijke, M. (2014). Fusion helps diversification. In SIGIR '14: proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval: July 6-11 2014, Gold Coast, Queensland, Australia (pp. 303-312). ACM. https://doi.org/10.1145/2600428.2609561 [details]
    • Liang, S., Ren, Z., & de Rijke, M. (2014). Personalized search result diversification via structured learning. In KDD'14: proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining: August 24-27, 2014, New York, NY, USA (pp. 751-760). Association for Computing Machinery. https://doi.org/10.1145/2623330.2623650 [details]
    • Liang, S., Ren, Z., & de Rijke, M. (2014). The impact of semantic document expansion on cluster-based fusion for microblog search. In M. de Rijke, T. Kenter, A. P. de Vries, C. X. Zhai, F. de Jong, K. Radinsky, & K. Hofmann (Eds.), Advances in Information Retrieval: 36th European Conference on IR Research, ECIR 2014, Amsterdam, The Netherlands, April 13-16, 2014: proceedings (pp. 493-499). (Lecture Notes in Computer Science). Springer. https://doi.org/10.1007/978-3-319-06028-6_47 [details]
    • Liang, S., Ren, Z., Weerkamp, W., Meij, E., & de Rijke, M. (2014). Time-aware rank aggregation for microblog search. In J. Li, & X. S. Wang (Eds.), CIKM '14: proceedings of the 2014 ACM International Conference on Information and Knowledge Management: November 3-7, 2014, Shanghai, China (pp. 989-998). Association for Computing Machinery. https://doi.org/10.1145/2661829.2661905 [details]
    • Markov, I., Kharitonov, E., Nikulin, V., Serdyukov, P., de Rijke, M., & Crestani, F. (2014). Vertical-aware click model-based effectiveness metrics. In J. Li, & X. S. Wang (Eds.), CIKM '14: proceedings of the 2014 ACM International Conference on Information and Knowledge Management: November 3-7, 2014, Shanghai, China (pp. 1867-1870). Association for Computing Machinery. https://doi.org/10.1145/2661829.2661944 [details]
    • Peetz, M. H., Meij, E., & de Rijke, M. (2014). Using temporal bursts for query modeling. Information Retrieval, 17(1), 74-108. Advance online publication. https://doi.org/10.1007/s10791-013-9227-2 [details]
    • Reinanda, R., & de Rijke, M. (2014). Prior-informed distant supervision for temporal evidence classification. In J. Tsujii, & J. Hajic (Eds.), COLING 2014: the 25th International Conference on Computational Linguistics: proceedings of COLING 2014 : technical papers: August 23-29, 2014, Dublin, Ireland (pp. 996-1006). Association for Computational Linguistics. http://www.aclweb.org/anthology/C/C14/C14-1094.pdf [details]
    • Ren, Z., Peetz, M. H., Liang, S., van Dolen, W., & de Rijke, M. (2014). Hierarchical multi-label classification of social text streams. In SIGIR '14: proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval: July 6-11 2014, Gold Coast, Queensland, Australia (pp. 213-222). ACM. https://doi.org/10.1145/2600428.2609595 [details]
    • Schuth, A., Sietsma, F., Whiteson, S., & de Rijke, M. (2014). Optimizing Base Rankers Using Clicks: A Case Study using BM25. In M. de Rijke, T. Kenter, A. P. de Vries, C. X. Zhai, F. de Jong, K. Radinsky, & K. Hofmann (Eds.), Advances in Information Retrieval: 36th European Conference on IR Research, ECIR 2014, Amsterdam, The Netherlands, April 13-16, 2014: proceedings (pp. 75-87). (Lecture Notes in Computer Science). Springer. https://doi.org/10.1007/978-3-319-06028-6_7 [details]
    • Schuth, A., Sietsma, F., Whiteson, S., Lefortier, D., & de Rijke, M. (2014). Multileaved Comparisons for Fast Online Evaluation. In J. Li, & X. S. Wang (Eds.), CIKM'14: proceedings of the 2014 ACM International Conference on Information and Knowledge Management: November 3-7, 2014, Shanghai, China (pp. 71-80). ACM. https://doi.org/10.1145/2661829.2661952 [details]
    • Severyn, A., Moschitti, A., Tsagkias, M., Berendsen, R., & de Rijke, M. (2014). A syntax-aware re-ranker for microblog retrieval. In SIGIR '14: proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval: July 6-11 2014, Gold Coast, Queensland, Australia (pp. 1067-1070). ACM. https://doi.org/10.1145/2600428.2609511 [details]
    • Voskarides, N., Odijk, D., Tsagkias, M., Weerkamp, W., & de Rijke, M. (2014). Query-dependent contextualization of streaming data. In M. de Rijke, T. Kenter, A. P. de Vries, C. X. Zhai, F. de Jong, K. Radinsky, & K. Hofmann (Eds.), Advances in Information Retrieval: 36th European Conference on IR Research, ECIR 2014, Amsterdam, The Netherlands, April 13-16, 2014: proceedings (pp. 706-712). (Lecture Notes in Computer Science). Springer. https://doi.org/10.1007/978-3-319-06028-6_80 [details]
    • Zoghi, M., Whiteson, S., Munos, R., & de Rijke, M. (2014). Relative Upper Confidence Bound for the K-Armed Dueling Bandit Problem. JMLR Workshop and Conference Proceedings, 32, 10-18. http://jmlr.org/proceedings/papers/v32/zoghi14.html [details]
    • Zoghi, M., Whiteson, S., de Rijke, M., & Munos, R. (2014). Relative confidence sampling for efficient on-line ranker evaluation. In WSDM '14: proceedings of the 7th ACM International Conference on Web Search and Data Mining: February 24-28, 2014, New York, New York, USA (pp. 73-82). ACM. https://doi.org/10.1145/2556195.2556256 [details]
    • de Rijke, M. (2014). Diversity, intent, and aggregated search. In J. S. Culpepper, L. Park, & G. Zuccon (Eds.), ADCS : proceedings of the 19th Australasian Document Computing Symposium: Melbourne, Australia, November 27-28, 2014 (pp. 1). ACM. https://doi.org/10.1145/2682862.2684462 [details]

    2013

    • Amigó, E., Carrillo de Albornoz, J., Chugur, I., Corujo, A., Gonzalo, J., Martín, T., Meij, E., de Rijke, M., & Spina, D. (2013). Overview of RepLab 2013: Evaluating online reputation monitoring systems. In P. Forner, H. Müller, R. Paredes, P. Rosso, & B. Stein (Eds.), Information Access Evaluation : Multilinguality, Multimodality, and Visualization: 4th International Conference of the CLEF Initiative, CLEF 2013, Valencia, Spain, September 23-26, 2013 : proceedings (pp. 333-352). (Lecture Notes in Computer Science; Vol. 8138). Springer. https://doi.org/10.1007/978-3-642-40802-1_31 [details]
    • Berendsen, R., Tsagkias, M., Weerkamp, W., & de Rijke, M. (2013). Pseudo Test Collections for Training and Tuning Microblog Rankers. In SIGIR '13: the proceedings of the 36th International ACM SIGIR Conference on Research & Development in Information Retrieval : July 28-August 1, 2013, Dublin, Ireland (pp. 53-62). ACM. https://doi.org/10.1145/2484028.2484063 [details]
    • Berendsen, R., de Rijke, M., Balog, K., Bogers, T., & van den Bosch, A. (2013). On the assessment of expertise profiles. Journal of the American Society for information Science and Technology, 64(10), 2024-2044. https://doi.org/10.1002/asi.22908 [details]
    • Bron, M., Balog, K., & de Rijke, M. (2013). Example Based Entity Search in the Web of Data. In P. Serdyukov, P. Braslavski, S. O. Kuznetsov, J. Kamps, S. Rüger, E. Agichtein, I. Segalovich, & E. Yilmaz (Eds.), Advances in Information Retrieval: 35th European Conference on IR Research, ECIR 2013, Moscow, Russia, March 24-27, 2013: proceedings (pp. 392-403). (Lecture Notes in Computer Science; Vol. 7814). Springer. https://doi.org/10.1007/978-3-642-36973-5_33 [details]
    • Bron, M., van Gorp, J., Nack, F., Baltussen, L. B., & de Rijke, M. (2013). Aggregated Search Interface Preferences in Multi-Session Search Tasks. In SIGIR '13: the proceedings of the 36th International ACM SIGIR Conference on Research & Development in Information Retrieval : July 28-August 1, 2013, Dublin, Ireland (pp. 123-132). ACM. https://doi.org/10.1145/2484028.2484050 [details]
    • Chuklin, A., Schuth, A., Hofmann, K., Serdyukov, P., & de Rijke, M. (2013). Evaluating aggregated search using interleaving. In CIKM'13: proceedings of the 22nd ACM International Conference on Information & Knowledge Management: Oct. 27- Nov. 1, 2013, San Francisco, CA, USA (pp. 669-678). Association for Computing Machinery. https://doi.org/10.1145/2505515.2505698 [details]
    • Chuklin, A., Serdyukov, P., & de Rijke, M. (2013). Click Model-Based Information Retrieval Metrics. In SIGIR '13: the proceedings of the 36th International ACM SIGIR Conference on Research & Development in Information Retrieval : July 28-August 1, 2013, Dublin, Ireland (pp. 493-502). ACM. https://doi.org/10.1145/2484028.2484071 [details]
    • Chuklin, A., Serdyukov, P., & de Rijke, M. (2013). Modeling clicks beyond the first result page. In CIKM'13: proceedings of the 22nd ACM International Conference on Information & Knowledge Management: Oct. 27- Nov. 1, 2013, San Francisco, CA, USA (pp. 1217-1220). Association for Computing Machinery. https://doi.org/10.1145/2505515.2507859 [details]
    • Chuklin, A., Serdyukov, P., & de Rijke, M. (2013). Using Intent Information to Model User Behavior in Diversified Search. In P. Serdyukov, P. Braslavski, S. O. Kuznetsov, J. Kamps, S. Rüger, E. Agichtein, I. Segalovich, & E. Yilmaz (Eds.), Advances in Information Retrieval: 35th European Conference on IR Research, ECIR 2013, Moscow, Russia, March 24-27, 2013: proceedings (pp. 1-13). (Lecture Notes in Computer Science; Vol. 7814). Springer. https://doi.org/10.1007/978-3-642-36973-5_1 [details]
    • Graus, D., Ren, Z., de Rijke, M., van Dijk, D., Henseler, H., & van der Knaap, N. (2013). Semantic Search in E-Discovery: An Interdisciplinary Approach. In ICAIL 2013 Workshop on Standards for Using Predictive Coding, Machine Learning, and Other Advanced Search and Review Methods in E-Discovery (DESI V Workshop): June 14, 2013, Casa dell'Aviatore, viale dell'Universita 20, Rome, Italy. Papers University of Maryland Institute for Advanced Computer Studies. http://www.umiacs.umd.edu/~oard/desi5/additional/Graus.pdf [details]
    • Hofmann, K., Schuth, A., Whiteson, S., & de Rijke, M. (2013). Reusing Historical Interaction Data for Faster Online Learning to Rank for IR. In WSDM 2013: proceedings of the 6th ACM International Conference on Web Search and Data Mining: February 4-8, 2013, Rome, Italy (pp. 183-192). ACM. https://doi.org/10.1145/2433396.2433419 [details]
    • Hofmann, K., Whiteson, S., & de Rijke, M. (2013). Balancing Exploration and Exploitation in Listwise and Pairwise Online Learning to Rank for Information Retrieval. Information Retrieval, 16(1), 63-90. https://doi.org/10.1007/s10791-012-9197-9 [details]
    • Hofmann, K., Whiteson, S., & de Rijke, M. (2013). Fidelity, Soundness, and Efficiency of Interleaved Comparison Methods. ACM Transactions on Information Systems, 31(4), Article 17. https://doi.org/10.1145/2536736.2536737 [details]
    • Kenter, T., Graus, D., Meij, E., & de Rijke, M. (2013). Time-Aware Chi-squared for Document Filtering over Time. In SIGIR 2013 Workshop on Time-aware Information Access: #TAIA2013: August 1, 2013 (pp. [18-21]). Microsoft Research. http://research.microsoft.com/en-us/people/milads/taia2013.proceedings.final.pdf [details]
    • Liang, S., & de Rijke, M. (2013). Finding Knowledgeable Groups in Enterprise Corpora. In SIGIR '13: the proceedings of the 36th International ACM SIGIR Conference on Research & Development in Information Retrieval : July 28-August 1, 2013, Dublin, Ireland (pp. 1005-1008). ACM. https://doi.org/10.1145/2484028.2484109 [details]
    • Liang, S., de Rijke, M., & Tsagkias, M. (2013). Late Data Fusion for Microblog Search. In P. Serdyukov, P. Braslavski, S. O. Kuznetsov, J. Kamps, S. Rüger, E. Agichtein, I. Segalovich, & E. Yilmaz (Eds.), Advances in Information Retrieval: 35th European Conference on IR Research, ECIR 2013, Moscow, Russia, March 24-27, 2013: proceedings (pp. 743-746). (Lecture Notes in Computer Science; Vol. 7814). Springer. https://doi.org/10.1007/978-3-642-36973-5_74 [details]
    • Odijk, D., Burscher, B., Vliegenthart, R., & de Rijke, M. (2013). Automatic thematic content analysis: finding frames in news. In A. Jatowt, E. P. Lim, Y. Ding, A. Miura, T. Tezuka, G. Dias, K. Tanaka, A. Flanagin, & B. T. Dai (Eds.), Social Informatics: 5th International Conference, SocInfo 2013, Kyoto, Japan, November 25-27, 2013: proceedings (pp. 333-345). (Lecture Notes in Computer Science; Vol. 8238). Springer. https://doi.org/10.1007/978-3-319-03260-3_29 [details]
    • Odijk, D., Meij, E., & de Rijke, M. (2013). Feeding the Second Screen: Semantic Linking based on Subtitles. In J. Ferreira, J. Magalhães, & P. Calado (Eds.), OAIR 2013: Open Research Areas in Information Retrieval: 10th Conference on the RIAO series (pp. 9-16). Centre de Hautes Etudes Internationales D'Informatique Documentaire. http://dl.acm.org/citation.cfm?id=2491751 [details]
    • Peetz, M-H., Spina, D., Gonzalo, J., & de Rijke, M. (2013). Towards an active learning system for company name disambiguation in microblog streams. In P. Forner, R. Navigli, D. Tufis, & N. Ferro (Eds.), Working Notes for CLEF 2013 Conference: Valencia, Spain, September 23-26, 2013 (CEUR Workshop Proceedings; Vol. 1179). CEUR-WS. http://ceur-ws.org/Vol-1179/CLEF2013wn-RepLab-PeetzEt2013.pdf [details]
    • Peetz, M. H., & de Rijke, M. (2013). Cognitive Temporal Document Priors. In P. Serdyukov, P. Braslavski, S. O. Kuznetsov, J. Kamps, S. Rüger, E. Agichtein, I. Segalovich, & E. Yilmaz (Eds.), Advances in Information Retrieval: 35th European Conference on IR Research, ECIR 2013, Moscow, Russia, March 24-27, 2013: proceedings (pp. 318-330). (Lecture Notes in Computer Science; Vol. 7814). Springer. https://doi.org/10.1007/978-3-642-36973-5_27 [details]
    • Reinanda, R., Odijk, D., & de Rijke, M. (2013). Exploring Entity Associations Over Time. In SIGIR 2013 Workshop on Time-aware Information Access: #TAIA2013: August 1, 2013 (pp. [30-33]). Microsoft Research. http://research.microsoft.com/en-us/people/milads/taia2013.proceedings.final.pdf [details]
    • Reinanda, R., Utama, M., Steijlen, F., & de Rijke, M. (2013). Entity Network Extraction based on Association Finding and Relation Extraction. In T. Aalberg, C. Papatheodorou, G. Tsakonas, & C. J. Farrugia (Eds.), Research and Advanced Technology for Digital Libraries: International Conference on Theory and Practice of Digital Libraries, TPDL 2013, Valletta, Malta, September 22-26, 2013: proceedings (pp. 156-167). (Lecture Notes in Computer Science; Vol. 8092). Springer. https://doi.org/10.1007/978-3-642-40501-3_16 [details]
    • Ren, Z., Liang, S., Meij, E., & de Rijke, M. (2013). Personalized Time-Aware Tweets Summarization. In SIGIR '13: the proceedings of the 36th International ACM SIGIR Conference on Research & Development in Information Retrieval : July 28-August 1, 2013, Dublin, Ireland (pp. 513-522). ACM. https://doi.org/10.1145/2484028.2484052 [details]
    • Ren, Z., van Dijk, D., Graus, D., van der Knaap, N., Henseler, H., & de Rijke, M. (2013). Semantic Linking and Contextualization for Social Forensic Text Analysis. In J. Brynielsson, & F. Johansson (Eds.), EISIC 2013: 2013 European Intelligence and Security Informatics Conference: proceedings: 12-14 August 2013, Uppsala, Sweden (pp. 96-99). Conference Publishing Services, IEEE Computer Society. https://doi.org/10.1109/EISIC.2013.21 [details]
    • Schuth, A., Hofmann, K., Whiteson, S., & de Rijke, M. (2013). Lerot: An Online Learning to Rank Framework. In LivingLab'13: Proceedings of the 2013 workshop on Living labs for information retrieval evaluation (pp. 23-26). ACM. https://doi.org/10.1145/2513150.2513162 [details]
    • Vossen, P., Maks, I., Segers, R., van Vliet, H., Moens, M-F., Hofmann, K., Tjong Kim Sang, E., & de Rijke, M. (2013). Cornetto: A Combinatorial Lexical Semantic Database for Dutch. In P. Spyns, & J. Odijk (Eds.), Essential speech and language technology for Dutch: results by the STEVIN programme (pp. 165-184). (Theory and applications of natural language processing). Springer. https://doi.org/10.1007/978-3-642-30910-6_10 [details]
    • Weerkamp, W., Tsagkias, M., & de Rijke, M. (2013). Inside the world's playlist. In CIKM'13: proceedings of the 22nd ACM International Conference on Information & Knowledge Management: Oct. 27- Nov. 1, 2013, San Francisco, CA, USA (pp. 2501-2504). Association for Computing Machinery. https://doi.org/10.1145/2505515.2508216 [details]
    • de Rijke, M., Jijkoun, V., Laan, F., Weerkamp, W., Ackermans, P., & Geleijnse, G. (2013). Generating, Refining and Using Sentiment Lexicons. In P. Spyns, & J. Odijk (Eds.), Essential speech and language technology for Dutch: results by the STEVIN programme (pp. 359-377). (Theory and applications of natural language processing). Springer. https://doi.org/10.1007/978-3-642-30910-6_20 [details]
    • de Rooij, O., Odijk, D., & de Rijke, M. (2013). ThemeStreams: Visualizing The Stream Of Themes Discussed In Politics. In SIGIR '13: the proceedings of the 36th International ACM SIGIR Conference on Research & Development in Information Retrieval : July 28-August 1, 2013, Dublin, Ireland (pp. 1077-1078). ACM. https://doi.org/10.1145/2484028.2484215 [details]

    2012

    • Amigó, E., Corujo, A., Gonzalo, J., Meij, E., & de Rijke, M. (2012). Overview of RepLab 2012: Evaluating Online Reputation Management Systems. In P. Forner, J. Karlgren, C. Womser-Hacker, & N. Ferro (Eds.), Working Notes for CLEF 2012 Conference: Rome, Italy, September 17-20, 2012 (CEUR Workshop Proceedings; Vol. 1178). CEUR-WS. http://ceur-ws.org/Vol-1178/CLEF2012wn-RepLab-AmigoEt2012.pdf [details]
    • Balog, K., Fang, Y., de Rijke, M., Serdyukov, P., & Si, L. (2012). Expertise Retrieval. Foundations and Trends in Information Retrieval, 6(2-3), 127-256. https://doi.org/10.1561/1500000024 [details]
    • Berendsen, R., Kovachev, B., Nastou, E., de Rijke, M., & Weerkamp, W. (2012). Result disambiguation in web people search. In R. Baeza-Yates, A. P. de Vries, H. Zaragoza, B. B. Cambazoglu, V. Murdock, R. Lempel, & F. Silvestri (Eds.), Advances in Information Retrieval: 34th European Conference on IR Research, ECIR 2012, Barcelona, Spain, April 1-5, 2012: proceedings (pp. 146-157). (Lecture Notes in Computer Science; Vol. 7224). Springer. https://doi.org/10.1007/978-3-642-28997-2_13 [details]
    • Berendsen, R., Meij, E., Odijk, D., de Rijke, M., & Weerkamp, W. (2012). The University of Amsterdam at TREC 2012. In E. M. Voorhees, & L. P. Buckland (Eds.), The Twenty-First Text REtrieval Conference (TREC 2012) Proceedings (NIST Special Publication; No. 500-298). National Institute of Standards and Technology. http://trec.nist.gov/pubs/trec21/papers/UvA.microblog.kba.final.pdf [details]
    • Berendsen, R., Tsagkias, M., de Rijke, M., & Meij, E. (2012). Generating pseudo test collections for learning to rank scientific articles. In T. Catarci, P. Forner, D. Hiemstra, A. Peñas, & G. Santucci (Eds.), Information Access Evaluation : Multilinguality, Multimodality, and Visual Analytics: third international conference of the CLEF Initiative, CLEF 2012: Rome, Italy, September 17-20 2012: proceedings (pp. 42-53). (Lecture Notes in Computer Science; Vol. 7488). Springer. https://doi.org/10.1007/978-3-642-33247-0_6 [details]
    • Bron, M., Nack, F., de Rijke, M., & van Gorp, J. (2012). Ingredients for a user interface to support media studies researchers in data collection. In M. L. Wilson, T. Russell-Rose, B. Larsen, & J. Kalbach (Eds.), Proceedings of the 2nd European Workshop on Human-Computer Interaction and Information Retrieval: Nijmegen, The Netherlands, August 25, 2012 (pp. 33-36). (CEUR Workshop Proceedings; Vol. 909). CEUR-WS. http://ceur-ws.org/Vol-909/paper9.pdf [details]
    • Bron, M., van Gorp, J., Nack, F., de Rijke, M., Vishneuski, A., & de Leeuw, S. (2012). A subjunctive exploratory search interface to support media studies researchers. In SIGIR'12: the proceedings of the International ACM SIGIR Conference on Research & Development in Information Retrieval: August 12-16, 2012: Portland, Oregon, USA (pp. 425-434). Association for Computing Machinery. https://doi.org/10.1145/2348283.2348342 [details]
    • Diaz, F., Dumais, S., Radinsky, K., de Rijke, M., & Shokouhi, M. (2012). #TAIA2012. SIGIR Forum, 46(2), 102-106. https://doi.org/10.1145/2422256.2422270 [details]
    • Ferro, N., Berendsen, R., Hanbury, A., Lupu, M., Petras, V., de Rijke, M., Silvello, G., Agosti, M., Bogers, T., Braschler, M., Buitelaar, P., Choukri, K., Di Nunzio, G. M., Forner, P., Friberg Heppin, K., Hansen, P., Järvelin, A., Larsen, B., Masiero, I., ... Toms, E. (2012). PROMISE Retreat Report: Prospects and Opportunities for Information Access Evaluation: Brainstorming workshop held on May 30-31, 2012, Padua, Italy. SIGIR Forum, 46(2), 60-84. https://doi.org/10.1145/2422256.2422265 [details]
    • Graus, D., Kenter, T., Bron, M., Meij, E., & de Rijke, M. (2012). Context-Based Entity Linking - University of Amsterdam at TAC 2012. In Proceedings of the Fifth Text Analysis Conference (TAC 2012): November 5-6, 2012, National Institute of Standards and Technology, Gaithersburg, Maryland, USA National Institute of Standards and Technology. http://www.nist.gov/tac/publications/2012/participant.papers/UvA.proceedings.pdf [details]
    • Hofmann, K., Whiteson, S., & de Rijke, M. (2012). Estimating interleaved comparison outcomes from historical click data. In CIKM’12: the proceedings of the 21st ACM International Conference on Information and Knowledge Management : October 29–November 2, 2012 Maui, Hawaii, USA (pp. 1779-1783). Association for Computing Machinery. https://doi.org/10.1145/2396761.2398516 [details]
    • Huurnink, B., Snoek, C. G. M., de Rijke, M., & Smeulders, A. W. M. (2012). Content-based analysis improves audiovisual archive retrieval. IEEE Transactions on Multimedia, 14(4), 1166-1178. https://doi.org/10.1109/TMM.2012.2193561 [details]
    • Meij, E., Weerkamp, W., & de Rijke, M. (2012). Adding semantics to microblog posts. In Proceedings of the 5th ACM International Conference on Web Search and Data Mining (pp. 563-572). ACM. https://doi.org/10.1145/2124295.2124364 [details]
    • Odijk, D., Santucci, G., de Rijke, M., Angelini, M., & Granato, G. L. (2012). Time-Aware Exploratory Search: Exploring Word Meaning through Time. In SIGIR 2012 Workshop on Time-aware Information Access: #TAIA2012. Accepted papers Microsoft Research. http://research.microsoft.com/en-us/people/milads/taia2012-visual.pdf [details]
    • Odijk, D., de Rooij, O., Peetz, M. H., Pieters, T., de Rijke, M., & Snelders, S. (2012). Semantic Document Selection: historical research on collections that span multiple centuries. In P. Zaphiris, G. Buchanan, E. Rasmussen, & F. Loizides (Eds.), Theory and Practice of Digital Libraries: second international conference, TPDL 2012, Paphos, Cyprus, September 23-27, 2012: proceedings (pp. 215-221). (Lecture Notes in Computer Science; Vol. 7489). Springer. https://doi.org/10.1007/978-3-642-33290-6_24 [details]
    • Oghina, A., Breuss, M., Tsagkias, M., & de Rijke, M. (2012). Predicting IMDB movie ratings using social media. In R. Baeza-Yates, A. P. de Vries, H. Zaragoza, B. B. Cambazoglu, V. Murdock, R. Lempel, & F. Silvestri (Eds.), Advances in Information Retrieval: 34th European Conference on IR Research, ECIR 2012, Barcelona, Spain, April 1-5, 2012: proceedings (pp. 503-507). (Lecture Notes in Computer Science; Vol. 7224). Springer. https://doi.org/10.1007/978-3-642-28997-2_51 [details]
    • Peetz, M-H., de Rijke, M., & Schuth, A. (2012). From Sentiment to Reputation: ILPS at RepLab 2012. In P. Forner, J. Karlgren, C. Womser-Hacker, & N. Ferro (Eds.), Working Notes for CLEF 2012 Conference: Rome, Italy, September 17-20, 2012 (CEUR Workshop Proceedings; Vol. 1178). CEUR-WS. http://ceur-ws.org/Vol-1178/CLEF2012wn-RepLab-PeetzEt2012.pdf [details]
    • Peetz, M. H., Meij, E., & de Rijke, M. (2012). OpenGeist: Insight in the Stream of Page Views on Wikipedia. In SIGIR 2012 Workshop on Time-aware Information Access: #TAIA2012. Accepted papers Microsoft Research. http://research.microsoft.com/en-us/people/milads/taia2012-opengeist-self-contained.pdf [details]
    • Peetz, M. H., Meij, E., de Rijke, M., & Weerkamp, W. (2012). Adaptive temporal query modeling. In R. Baeza-Yates, A. P. de Vries, H. Zaragoza, B. B. Cambazoglu, V. Murdock, R. Lempel, & F. Silvestri (Eds.), Advances in Information Retrieval: 34th European Conference on IR Research, ECIR 2012, Barcelona, Spain, April 1-5, 2012: proceedings (pp. 455-458). (Lecture Notes in Computer Science; Vol. 7224). Springer. https://doi.org/10.1007/978-3-642-28997-2_40 [details]
    • Spina, D., Meij, E., Oghina, A., Bui, M. T., Breuss, M., & de Rijke, M. (2012). A Corpus for Entity Profiling in Microblog Posts. In A. Corujo, J. Gonzalo, E. Meij, M. de Rijke, & I. Chugur (Eds.), Language Engineering for Online Reputation Management: 26 May 2012: proceedings (pp. 30-34). European Language Resources Association (ELRA). http://www.lrec-conf.org/proceedings/lrec2012/workshops/15.LREC%202012%20Online%20Reputation%20Proceedings.pdf [details]
    • Spina, D., Meij, E., de Rijke, M., Oghina, A., Bui, M. T., & Breuss, M. (2012). Identifying Entity Aspects in Microblog Posts. In SIGIR'12: the proceedings of the International ACM SIGIR Conference on Research & Development in Information Retrieval: August 12-16, 2012: Portland, Oregon, USA (pp. 1089-1090). Association for Computing Machinery. https://doi.org/10.1145/2348283.2348483 [details]
    • Weerkamp, W., & de Rijke, M. (2012). Activity Prediction: A Twitter-based Exploration. In SIGIR 2012 Workshop on Time-aware Information Access: #TAIA2012. Accepted papers Microsoft Research. http://research.microsoft.com/en-us/people/milads/taia2012-activities.pdf [details]
    • Weerkamp, W., & de Rijke, M. (2012). Credibility-inspired Ranking for Blog Post Retrieval. Information Retrieval, 15(3-4), 243-277. Advance online publication. https://doi.org/10.1007/s10791-011-9182-8 [details]
    • Weerkamp, W., Balog, K., & de Rijke, M. (2012). Exploiting External Collections for Query Expansion. ACM Transactions on the Web, 6(4), 18. https://doi.org/10.1145/2382616.2382621 [details]
    • de Goede, B., Schuth, A., & de Rijke, M. (2012). Sustainable Questions: Determining the Expiration Date of Answers. In SIGIR 2012 Workshop on Time-aware Information Access: #TAIA2012. Accepted papers Microsoft Research. http://research.microsoft.com/en-us/people/milads/taia2012-sustainable.pdf [details]
    • de Rooij, O., Vishneuski, A., & de Rijke, M. (2012). xTAS: text analysis in a timely manner. In DIR 2012: Ghent, 23-24 February 2012: 12th Dutch-Belgian Information Retrieval Workshop (pp. 89-90). University of Ghent. http://dir2012.intec.ugent.be/system/files/proceedings/DIR_2012_Proceedings.pdf [details]

    2011

    • Balog, K., Bron, M., & de Rijke, M. (2011). Query modeling for entity search based on terms, categories and examples. ACM Transactions on Information Systems, 29(4), Article 22. https://doi.org/10.1145/2037661.2037667 [details]
    • Berendsen, R., Kovachev, B., Meij, E., de Rijke, M., & Weerkamp, W. (2011). Classifying queries submitted to a vertical search engine. In Proceedings of the 3rd International Web Science Conference: WebSci '11 (pp. 4). ACM. https://doi.org/10.1145/2527031.2527055 [details]
    • Bron, M., Huurnink, B., & de Rijke, M. (2011). Linking archives using document enrichment and term selection. In S. Gradmann, F. Borri, C. Meghini, & H. Schuldt (Eds.), Research and Advanced Technology for Digital Libraries: International Conference on Theory and Practice of Digital Libraries, TPDL 2011, Berlin, Germany, September 26-28, 2011: proceedings (pp. 360-371). (Lecture Notes in Computer Science; Vol. 6966). Springer. https://doi.org/10.1007/978-3-642-24469-8_37 [details]
    • Bron, M., van Gorp, J., Nack, F., & de Rijke, M. (2011). Exploratory search in an audio-visual archive: evaluating a professional search tool for non-professional users. In EuroHCIR 2011: 1st European Workshop on Human-Computer Interaction and Information Retrieval (pp. 3-6) [details]
    • He, J., Bron, M., & de Rijke, M. (2011). A query performance analysis for result diversification. In G. Amati, & F. Crestani (Eds.), Advances in Information Retrieval Theory: Third International Conference, ICTIR 2011, Bertinoro, Italy, September 12-14, 2011 : proceedings (pp. 351-355). (Lecture Notes in Computer Science; Vol. 6931). Springer. https://doi.org/10.1007/978-3-642-23318-0_37 [details]
    • He, J., Meij, E., & de Rijke, M. (2011). Result diversification based on query-specific cluster ranking. Journal of the American Society for information Science and Technology, 62(3), 550-571. https://doi.org/10.1002/asi.21468 [details]
    • He, J., de Rijke, M., Sevenster, M., van Ommering, R., & Qian, Y. (2011). Generating links to background knowledge: a case study using narrative radiology reports. In CIKM'11: proceedings of the 2011 ACM International Conference on Information and Knowledge Management : October 24-28, 2011, Glasgow, Scotland (pp. 1867-1876). Association for Computing Machinery. https://doi.org/10.1145/2063576.2063845 [details]
    • Hofmann, K., Whiteson, S., & de Rijke, M. (2011). A Probabilistic Method for Inferring Preferences from Clicks. In CIKM'11: proceedings of the 2011 ACM International Conference on Information and Knowledge Management : October 24-28, 2011, Glasgow, Scotland (pp. 249-258). Association for Computing Machinery. https://doi.org/10.1145/2063576.2063618 [details]
    • Hofmann, K., Whiteson, S., & de Rijke, M. (2011). Balancing exploration and exploitation in learning to rank online. In P. Clough, C. Foley, C. Gurrin, G. J. F. Jones, W. Kraaij, H. Lee, & V. Murdoch (Eds.), Advances in Information Retrieval: 33rd European Conference on IR Research, ECIR 2011, Dublin, Ireland, April 18-21, 2011 : proceedings (pp. 251-263). (Lecture Notes in Computer Science; Vol. 6611). Springer. https://doi.org/10.1007/978-3-642-20161-5_25 [details]
    • Hofmann, K., Whiteson, S., & de Rijke, M. (2011). Contextual Bandits for Information Retrieval. In NIPS 2011: Proceedings of the Conference on Neural Information Processing Systems, Workshop on Bayesian Optimization, Experimental Design and Bandits: Theory and Applications (pp. 1-5). NIPS. http://staff.science.uva.nl/~whiteson/pubs/hofmannnips11.pdf [details]
    • Jijkoun, V., & de Rijke, M. (2011). Bootstrapping subjectivity detection. In SIGIR'11: proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval ; July 24-28, 2011, Beijing, China (pp. 1125-1126). ACM. https://doi.org/10.1145/2009916.2010081 [details]
    • Massoudi, K., Tsagkias, M., de Rijke, M., & Weerkamp, W. (2011). Incorporating query expansion and quality indicators in searching microblog posts. In P. Clough, C. Foley, C. Gurrin, G. J. F. Jones, W. Kraaij, H. Lee, & V. Murdoch (Eds.), Advances in Information Retrieval: 33rd European Conference on IR Research, ECIR 2011, Dublin, Ireland, April 18-21, 2011 : proceedings (pp. 362-367). (Lecture Notes in Computer Science; Vol. 6611). Springer. https://doi.org/10.1007/978-3-642-20161-5_36 [details]
    • Meij, E., & de Rijke, M. (2011). Wij-woorden op websites: zoekmachines voor geesteswetenschappers. In J. Verheijen, & J. Bekkenkamp (Eds.), Onszelf voorbij: over de grenzen van verbondenheid (pp. 217-239, 260). Parthenon. [details]
    • Meij, E., Bron, M., Hollink, L., Huurnink, B., & de Rijke, M. (2011). Mapping queries to the Linking Open Data cloud: a case study using DBpedia. Journal of Web Semantics, 9(4), 418-433. https://doi.org/10.1016/j.websem.2011.04.001 [details]
    • Tjong Kim Sang, E., Hofmann, K., & de Rijke, M. (2011). Extraction of hypernymy information from text. In A. van den Bosch, & G. Bouma (Eds.), Interactive Multi-modal Question-Answering (pp. 223-245). (Theory and Applications of Natural Language Processing). Springer. https://doi.org/10.1007/978-3-642-17525-1_10 [details]
    • Tsagkias, M., de Rijke, M., & Weerkamp, W. (2011). Hypergeometric language models for republished article finding. In SIGIR'11: proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval ; July 24-28, 2011, Beijing, China (pp. 485-494). ACM. https://doi.org/10.1145/2009916.2009983 [details]
    • Tsagkias, M., de Rijke, M., & Weerkamp, W. (2011). Linking online news and social media. In Proceedings of the fourth ACM international conference on Web search and data mining (pp. 565-574). ACM. https://doi.org/10.1145/1935826.1935906 [details]
    • Weerkamp, W., Balog, K., & de Rijke, M. (2011). Blog feed search with a post index. Information Retrieval, 14(5), 515-545. https://doi.org/10.1007/s10791-011-9165-9 [details]
    • Weerkamp, W., Berendsen, R., Kovachev, B., Meij, E., Balog, K., & de Rijke, M. (2011). People searching for people: analysis of a people search engine log. In SIGIR'11: proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval ; July 24-28, 2011, Beijing, China (pp. 45-54). ACM. https://doi.org/10.1145/2009916.2009927 [details]
    • de Rijke, M. (2011). DuOMAn: Dutch language online media analysis. In STEVIN Programme Project Results (pp. 38-39). NTU. http://ilps.science.uva.nl/sites/default/files/STEVIN%20Resultatenboek%20DuOMAn.pdf [details]
    • van Dijk, D., Henseler, H., & de Rijke, M. (2011). Semantic search in E-Discovery: research on the application of text mining and information retrieval for fact finding in regulatory investigations. In ICAIL 2011/DESI IV: Workshop on Setting Standards for Searching Electronically Stored Information in Discovery Proceedings: June 6, 2011: Thirteenth International Conference on Artificial Intelligence and Law: ICAIL 2011: University of Pittsburgh School of Law, Pittsburgh PA (pp. [109-112]). University of Maryland Institute for Advanced Computer Studies. http://www.umiacs.umd.edu/~oard/desi4/proceedings.pdf [details]

    2010

    • Agosti, M., Braschler, M., Choukri, K., Ferro, N., Harman, D., Peters, C., Pianta, E., de Rijke, M., & Smeaton, A. (2010). CLEF 2010: Conference on Multilingual and Multimodal Information Access Evaluation. SIGIR Forum, 44(2), 8-12. https://doi.org/10.1145/1924475.1924477 [details]
    • Balog, K., Bron, M., & de Rijke, M. (2010). Category-based query modeling for entity search. In C. Gurrin, Y. He, G. Kazai, U. Kruschwitz, S. Little, T. Roelleke, S. Rüger, & K. van Rijsbergen (Eds.), Advances in Information Retrieval: 32nd European Conference on IR Research, ECIR 2010, Milton Keynes, UK, March 28-31, 2010: proceedings (pp. 319-331). (Lecture Notes in Computer Science; Vol. 5993). Springer. https://doi.org/10.1007/978-3-642-12275-0_29 [details]
    • Balog, K., Bron, M., de Rijke, M., & Weerkamp, W. (2010). Combining term-based and category-based representations for entity search. In S. Geva, J. Kamps, & A. Trotman (Eds.), Focused Retrieval and Evaluation: 8th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2009, Brisbane, Australia, December 7-9, 2009 : revised and selected papers (pp. 265-272). (Lecture Notes in Computer Science; Vol. 6203). Springer. https://doi.org/10.1007/978-3-642-14556-8_27 [details]
    • Balog, K., Meij, E., & de Rijke, M. (2010). Entity search: building bridges between two worlds. In SemSearch2010: Semantic Search 2010 Workshop at WWW 2010, Raleigh, NC (pp. 9). ACM. https://doi.org/10.1145/1863879.1863888 [details]
    • Braschler, M., Choukri, K., Ferro, N., Hanbury, A., Karlgren, J., Müller, H., Petras, V., Pianta, E., de Rijke, M., & Santucci, G. (2010). A PROMISE for experimental evaluation. In M. Agosti, N. Ferro, C. Peters, M. de Rijke, & A. Smeaton (Eds.), Multilingual and Multimodal Information Access Evaluation: international conference of the Cross-Language Evaluation Forum, CLEF 2010, Padua, Italy, September 20-23, 2010 : proceedings (pp. 140-144). (Lecture Notes in Computer Science; Vol. 6360). Springer. https://doi.org/10.1007/978-3-642-15998-5_16 [details]
    • Bron, M., Balog, K., & de Rijke, M. (2010). Ranking related entities: components and analyses. In X. J. Huang, G. Jones, N. Koudas, X. Wu, & K. Collins-Thompson (Eds.), CIKM '10: proceedings of the 19th International Conference on Information & Knowledge Management and Co-Located Workshops : October 26-30, 2010, Toronto, Ontario, Canada (pp. 1079-1088). ACM. https://doi.org/10.1145/1871437.1871574 [details]
    • He, J., & de Rijke, M. (2010). An exploration of learning to link with Wikipedia: features, methods and training collection. In S. Geva, J. Kamps, & A. Trotman (Eds.), Focused Retrieval and Evaluation: 8th International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2009, Brisbane, Australia, December 7-9, 2009 : revised and selected papers (pp. 324-330). (Lecture Notes in Computer Science; Vol. 6203). Springer. https://doi.org/10.1007/978-3-642-14556-8_32 [details]
    • Hofmann, K., Balog, K., Bogers, T., & de Rijke, M. (2010). Contextual factors for finding similar experts. Journal of the American Society for information Science and Technology, 61(5), 994-1014. https://doi.org/10.1002/asi.21292 [details]
    • Huurnink, B., Hofmann, K., & de Rijke, M. (2010). Simulating searches from transaction logs. In L. Azzopardi, K. Järvelin, J. Kamps, & M. D. Smucker (Eds.), Proceedings of the SIGIR 2010 Workshop on the Simulation of Interaction: Automated Evaluation of Interactive IR : Geneva, Switzerland, July 19-23, 2010 (pp. 21-22). IR Publications. http://staff.science.uva.nl/~kamps/publications/2010/azzo:simu10.pdf [details]
    • Huurnink, B., Hofmann, K., de Rijke, M., & Bron, M. (2010). Validating query simulators: an experiment using commercial searches and purchases. In M. Agosti, N. Ferro, C. Peters, M. de Rijke, & A. Smeaton (Eds.), Multilingual and Multimodal Information Access Evaluation: international conference of the Cross-Language Evaluation Forum, CLEF 2010, Padua, Italy, September 20-23, 2010 : proceedings (pp. 40-51). (Lecture Notes in Computer Science; Vol. 6360). Springer. https://doi.org/10.1007/978-3-642-15998-5_6 [details]
    • Huurnink, B., Hollink, L., van den Heuvel, W., & de Rijke, M. (2010). Search behavior of media professionals at an audiovisual archive: A transaction log analysis. Journal of the American Society for information Science and Technology, 61(6), 1180-1197. https://doi.org/10.1002/asi.21327 [details]
    • Huurnink, B., Snoek, C. G. M., de Rijke, M., & Smeulders, A. W. M. (2010). Today's and tomorrow's retrieval practice in the audiovisual archive. In CIVR 2010: 2010 ACM International Conference on Image and Video Retrieval, at Xi'an, China, July 5-7, 2010 (pp. 18-25). Association for Computing Machinery. https://doi.org/10.1145/1816041.1816045 [details]
    • Jijkoun, V., Weerkamp, W., de Rijke, M., Ackermans, P., & Geleijnse, G. (2010). Mining user experiences from online forums: an exploration. In NAACL HLT 2010 workshop on Computational Linguistics in a World of Social Media (#SocialMedia 2010) (pp. 17-18). Association for Computational Linguistics (ACL). http://www.aclweb.org/anthology/W/W10/W10-0509.pdf [details]
    • Jijkoun, V., de Rijke, M., & Weerkamp, W. (2010). Generating focused topic-specific sentiment lexicons. In J. Hajič, S. Carberry, S. Clark, & J. Nivre (Eds.), 48th Annual Meeting of the Association for Computational Linguistics : ACL 2010: proceedings of the conference : 11-16 July 2010, Uppsala University, Uppsala, Sweden (Vol. 1, pp. 585-594). Association for Computational Linguistics. http://www.aclweb.org/anthology-new/P/P10/P10-1060.pdf [details]
    • Meij, E., Trieschnigg, D., de Rijke, M., & Kraaij, W. (2010). Conceptual language models for domain-specific retrieval. Information Processing & Management, 46(4), 448-469. https://doi.org/10.1016/j.ipm.2009.09.005 [details]
    • Snoek, C. G. M., van de Sande, K. E. A., de Rooij, O., Huurnink, B., Gavves, E., Odijk, D., de Rijke, M., Gevers, T., Worring, M., Koelma, D. C., & Smeulders, A. W. M. (2010). The MediaMill TRECVID 2010 semantic video search engine. In TRECVID 2010 notebook National Institute of Standards and Technology. http://www-nlpir.nist.gov/projects/tvpubs/tv10.papers/mediamill.pdf [details]
    • Tsagkias, M., Larson, M., & de Rijke, M. (2010). Predicting podcast preference: An analysis framework and its application. Journal of the American Society for information Science and Technology, 61(2), 374-391. https://doi.org/10.1002/asi.21259 [details]
    • Tsagkias, M., Weerkamp, W., & de Rijke, M. (2010). News comments: exploring, modeling, and online prediction. In C. Gurrin, Y. He, G. Kazai, U. Kruschwitz, S. Little, T. Roelleke, S. Rüger, & K. van Rijsbergen (Eds.), Advances in Information Retrieval: 32nd European Conference on IR Research, ECIR 2010, Milton Keynes, UK, March 28-31, 2010: proceedings (pp. 191-203). (Lecture Notes in Computer Science; Vol. 5993). Springer. https://doi.org/10.1007/978-3-642-12275-0_19 [details]
    • Weerkamp, W., Balog, K., & de Rijke, M. (2010). A two-stage model for blog feed search. In 33rd Annual International ACM SIGIR Conference (SIGIR 2010), Geneva, Switzerland (pp. 877-878). ACM. https://doi.org/10.1145/1835449.1835661 [details]
    • de Rijke, M., Balog, K., Bogers, T., & van den Bosch, A. (2010). On the evaluation of entity profiles. In M. Agosti, N. Ferro, C. Peters, M. de Rijke, & A. Smeaton (Eds.), Multilingual and Multimodal Information Access Evaluation: international conference of the Cross-Language Evaluation Forum, CLEF 2010, Padua, Italy, September 20-23, 2010 : proceedings (pp. 94-99). (Lecture Notes in Computer Science; Vol. 6360). Springer. https://doi.org/10.1007/978-3-642-15998-5_11 [details]

    2009

    • Balog, K., Azzopardi, L., & de Rijke, M. (2009). A language modeling framework for expert finding. Information Processing & Management, 45(1), 1-19. https://doi.org/10.1016/j.ipm.2008.06.003 [details]
    • Balog, K., Azzopardi, L., & de Rijke, M. (2009). Resolving person names in web people search. In I. King, & R. Baeza-Yates (Eds.), Weaving services and people on the World Wide Web (pp. 301-323). Springer. https://doi.org/10.1007/978-3-642-00570-1_15 [details]
    • Fissaha Adafre, S., de Rijke, M., & Tjong Kim Sang, E. (2009). Completing lists of entities. Amsterdam Studies in the Theory and History of Linguistic Science. Series 4, Current Issues in Linguistic Theory, 309, 181-192. https://doi.org/10.1075/cilt.309 [details]
    • He, J., Weerkamp, W., Larson, M., & de Rijke, M. (2009). An effective coherence measure to determine topical consistency in user-generated content. International Journal on Document Analysis and Recognition, 12(3), 185-203. https://doi.org/10.1007/s10032-009-0089-5 [details]
    • Hofmann, K., Tsagkias, M., Meij, E., & de Rijke, M. (2009). The impact of document structure on keyphrase extraction. In D. Cheung, I-Y. Song, W. Chu, X. Hu, J. Lin, J. Li, & Z. Peng (Eds.), Proceedings of the 18th ACM Conference on Information and Knowledge Management, Hong Kong (pp. 1725-1728). ACM. https://doi.org/10.1145/1645953.1646215 [details]
    • Hollink, L., Schreiber, G., Huurnink, B., van Liempt, M., de Rijke, M., Smeulders, A., Oomen, J., & de Jong, A. (2009). A multidisciplinary approach to unlocking television broadcast archives. ISR Interdisciplinary Science Reviews, 34(2-3), 253-267. https://doi.org/10.1179/174327909X441144 [details]
    • Jijkoun, V., & de Rijke, M. (2009). Overview of WebCLEF 2008. In C. Peters, T. Deselaers, N. Ferro, J. Gonzalo, G. J. F. Jones, M. Kurimo, T. Mandl, A. Peñas, & V. Petras (Eds.), Evaluating Systems for Multilingual and Multimodal Information Access: 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Aarhus, Denmark, September 17-19, 2008 : revised selected papers (pp. 787-793). (Lecture Notes in Computer Science; Vol. 5706). Springer. https://doi.org/10.1007/978-3-642-04447-2_102 [details]
    • Larson, M., Tsagkias, M., He, J., & de Rijke, M. (2009). Investigating the global semantic impact of speech recognition error on spoken content collections. In M. Boughanem, C. Berrut, J. Mothe, & C. Soule-Dupuy (Eds.), Advances in Information Retrieval: 31th European Conference on IR Research, ECIR 2009, Toulouse, France, April 6-9, 2009 : proceedings (pp. 755-760). (Lecture Notes in Computer Science; Vol. 5478). Springer. https://doi.org/10.1007/978-3-642-00958-7_80 [details]
    • Meij, E., & de Rijke, M. (2009). Concept models for domain-specific search. In C. Peters, T. Deselaers, N. Ferro, J. Gonzalo, G. J. F. Jones, M. Kurimo, T. Mandl, A. Peñas, & V. Petras (Eds.), Evaluating Systems for Multilingual and Multimodal Information Access: 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Aarhus, Denmark, September 17-19, 2008 : revised selected papers (pp. 207-214). (Lecture Notes in Computer Science; Vol. 5706). Springer. https://doi.org/10.1007/978-3-642-04447-2_26 [details]
    • Meij, E., Bron, M., Hollink, L., Huurnink, B., & de Rijke, M. (2009). Learning semantic query suggestions. In A. Bernstein, D. R. Karger, T. Heath, L. Feigenbaum, D. Maynard, E. Motta, & K. Thirunarayan (Eds.), The Semantic Web - ISWC 2009: 8th International Semantic Web Conference, ISWC 2009, Chantilly, VA, USA, October 25-29, 2009 : proceedings (pp. 424-440). (Lecture Notes in Computer Science; Vol. 5823). Springer. https://doi.org/10.1007/978-3-642-04930-9_27 [details]
    • Meij, E., Weerkamp, W., & de Rijke, M. (2009). A query model based on normalized log-likelihood. In D. Cheung, I-Y. Song, W. Chu, X. Hu, J. Lin, J. Li, & Z. Peng (Eds.), Proceedings of the 18th ACM Conference on Information and Knowledge Management, Hong Kong (pp. 1903-1906). ACM. http://doi.acm.org/10.1145/1645953.1646261 [details]
    • Snoek, C. G. M., van de Sande, K. E. A., de Rooij, O., Huurnink, B., Uijlings, J. R. R., van Liempt, M., Bugalho, M., Trancoso, I., Yan, F., Tahir, M. A., Mikolajczyk, K., Kittler, J., de Rijke, M., Geusebroek, J. M., Gevers, T., Worring, M., Smeulders, A. W. M., & Koelma, D. C. (2009). The MediaMill TRECVID 2009 semantic video search engine. In TRECVID 2009 Overview Papers and Slides National Institute of Standards and Technology (NIST). http://www-nlpir.nist.gov/projects/tvpubs/tv9.papers/mediamill.pdf [details]
    • Tsagkias, M., Larson, M., & de Rijke, M. (2009). Exploiting surface features for the prediction of podcast preference. In M. Boughanem, C. Berrut, J. Mothe, & C. Soule-Dupuy (Eds.), Advances in Information Retrieval: 31th European Conference on IR Research, ECIR 2009, Toulouse, France, April 6-9, 2009 : proceedings (pp. 473-484). (Lecture Notes in Computer Science; Vol. 5478). Springer. https://doi.org/10.1007/978-3-642-00958-7_42 [details]
    • Tsagkias, M., Weerkamp, W., & de Rijke, M. (2009). Predicting the volume of comments on online news stories. In D. Cheung, I-Y. Song, W. Chu, X. Hu, J. Lin, J. Li, & Z. Peng (Eds.), Proceedings of the 18th ACM Conference on Information and Knowledge Management, Hong Kong (pp. 1765-1768). ACM. http://doi.acm.org/10.1145/1645953.1646225 [details]
    • Weerkamp, W., Balog, K., & de Rijke, M. (2009). A generative blog post retrieval model that uses query expansion based on external collections. In K-Y. Su, J. Su, J. Wiebe, & H. Li (Eds.), Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP, Suntec, Singapore: Volume 2 (pp. 1057-1065). Association for Computational Linguistics (ACL). http://portal.acm.org/citation.cfm?id=1690294 [details]
    • Weerkamp, W., Balog, K., & de Rijke, M. (2009). Using contextual information to improve search in email archives. In M. Boughanem, C. Berrut, J. Mothe, & C. Soule-Dupuy (Eds.), Advances in Information Retrieval: 31th European Conference on IR Research, ECIR 2009, Toulouse, France, April 6-9, 2009 : proceedings (pp. 400-411). (Lecture Notes in Computer Science; Vol. 5478). Springer. https://doi.org/10.1007/978-3-642-00958-7_36 [details]

    2008

    • Balog, K., & de Rijke, M. (2008). Associating people and documents. In C. Macdonald, I. Ounis, V. Plachouras, I. Ruthven, & R. W. White (Eds.), Advances in Information Retrieval: 30th European Conference on IR Research, ECIR 2008, Glasgow, UK, March 30-April 3, 2008 : proceedings (pp. 296-308). (Lecture Notes in Computer Science; Vol. 4956). Springer. https://doi.org/10.1007/978-3-540-78646-7_28 [details]
    • Balog, K., & de Rijke, M. (2008). Non-local evidence for expert finding. In J. G. Shanahan, S. Amer-Yahia, Y. Zhang, A. Kołcz, A. Chowdury, & D. Kelly (Eds.), CIKM 2008: ACM 17th Conference on Information and Knowledge Management: October 26-30, 2008, Napa Valley, California (pp. 489-498). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1458082.1458148 [details]
    • Balog, K., Weerkamp, W., & de Rijke, M. (2008). A few examples go a long way: Constructing query models from elaborate query formulations. In S-H. Myaeng, D. W. Oard, F. Sebastiani, T-S. Chua, & M-K. Leong (Eds.), ACM SIGIR 2008: Thirty-first Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 20-24 July 2008, Singapore: Proceedings (pp. 371-378). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1390334.1390399 [details]
    • Balog, K., de Rijke, M., & Weerkamp, W. (2008). Bloggers as experts. In S-H. Myang, D. W. Oard, F. Sebastiani, T-S. Chua, & M-K. Leong (Eds.), ACM SIGIR 2008: Thirty-first Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 20-24 July 2008, Singapore: Proceedings (pp. 753-754). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1390334.1390486 [details]
    • Elgersma, E., & de Rijke, M. (2008). Personal vs non-personal blogs: Initial classification experiments. In S-H. Myaeng, D. W. Oard, F. Sebastiani, T-S. Chua, & M-K. Leong (Eds.), ACM SIGIR 2008: Thirty-first Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 20-24 July 2008, Singapore: Proceedings (pp. 723-724). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1390334.1390471 [details]
    • Fuller, M., Tsagkias, E., Newman, E., Besser, J., Larson, M., Jones, G. J. F., & de Rijke, M. (2008). Using term clouds to represent segment-level semantic content of podcasts. In J. Köhler, M. Larson, F. M. G. de Jong, W. Kraaij, & R. J. F. Ordelman (Eds.), Proceedings of the ACM SIGIR Workshop 'Searching Spontaneous Conversational Speech' (pp. 12-19). Centre for Telematics and Information Technology (CTIT). http://ilps.science.uva.nl/SSCS2008/Proceedings/sscs08_proceedings.pdf [details]
    • He, J., Larson, M., & de Rijke, M. (2008). On the topical structure of the relevance feedback set. In T. Mandl, N. Fuhr, & A. Henrich (Eds.), Proceedings: Workshop Information Retrieval 2008, 6.-8. October 2008, University of Würzburg, Germany (pp. 69-72). Gesellschaft für Informatik, special interest group Information Retrieval. http://www.uni-hildesheim.de/~fgir/fgir-Dateien/WIR2008ProceedingsLWAWuerzburg.pdf [details]
    • He, J., Larson, M., & de Rijke, M. (2008). Using coherence-based measures to predict query difficulty. In C. Macdonald, I. Ounis, V. Plachouras, I. Ruthven, & R. W. White (Eds.), Advances in Information Retrieval: 30th European Conference on IR Research, ECIR 2008, Glasgow, UK, March 30-April 3, 2008 : proceedings (pp. 689-694). (Lecture Notes in Computer Science; Vol. 4956). Springer. https://doi.org/10.1007/978-3-540-78646-7_80 [details]
    • He, J., Weerkamp, W., Larson, M., & de Rijke, M. (2008). Blogger, stick to your story: Modeling topical noise in blogs with coherence measures. ACM International Conference Proceedings Series, 303, 39-46. https://doi.org/10.1145/1390749.1390757 [details]
    • Hofmann, K., Balog, K., Bogers, T., & de Rijke, M. (2008). Integrating contextual factors into topic-centric retrieval models for finding similar experts. In fCHER: SIGIR 2008 Workshop on Future Challenges in Expertise Retrieval: Proceedings (pp. 29-36) http://ilps.science.uva.nl/fCHER/files/fcher.hofmann.pdf [details]
    • Huurnink, B., Hofmann, K., & de Rijke, M. (2008). Assessing concept selection for video retrieval. In Proceedings of the 1st ACM International Conference on Multimedia Information Retrieval (MIR 2008) (pp. 459-466). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1460096.1460170 [details]
    • Jijkoun, V., & de Rijke, M. (2008). Overview of WebCLEF 2007. In C. Peters, V. Jijkoun, T. Mandl, H. Müller, D. W. Oard, A. Peñas, A. Petras, & D. Santos (Eds.), Advances in multilingual and multimodal information retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007: Revised selected papers (pp. 725-731). (Lecture Notes in Computer Science; No. 5152). Springer. https://doi.org/10.1007/978-3-540-85760-0_92 [details]
    • Jijkoun, V., & de Rijke, M. (2008). Using centrality to rank web snippets. In C. Peters, V. Jijkoun, T. Mandl, H. Müller, D. W. Oard, A. Peñas, V. Petras, & D. Santos (Eds.), Advances in multilingual and multimodal information retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007: Revised selected papers (pp. 737-741). (Lecture Notes in Computer Science; No. 5152). Springer. https://doi.org/10.1007/978-3-540-85760-0_94 [details]
    • Jijkoun, V., Hofmann, K., Ahn, D., Khalid, M. A., van Rantwijk, J., de Rijke, M., & Tjong Kim Sang, E. (2008). The University of Amsterdam's question answering system at QA@CLEF 2007. In C. Peters, V. Jijkoun, T. Mandl, H. Müller, D. W. Oard, A. Peñas, V. Petras, & D. Santos (Eds.), Advances in multilingual and multimodal information retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007: Revised selected papers (pp. 344-351). (Lecture Notes in Computer Science; No. 5152). Springer. https://doi.org/10.1007/978-3-540-85760-0_43 [details]
    • Jijkoun, V., Khalid, M. A., Marx, M., & de Rijke, M. (2008). Named entity normalization in user generated content. ACM International Conference Proceedings Series, 303, 23-30. https://doi.org/10.1145/1390749.1390755 [details]
    • Khalid, M. A., Jijkoun, V., & de Rijke, M. (2008). The impact of named entity normalization on information retrieval for question answering. In C. Macdonald, I. Ounis, V. Plachouras, I. Ruthven, & R. W. White (Eds.), Advances in Information Retrieval: 30th European Conference on IR Research, ECIR 2008, Glasgow, UK, March 30-April 3, 2008 : proceedings (pp. 705-710). (Lecture Notes in Computer Science; Vol. 4956). Springer. https://doi.org/10.1007/978-3-540-78646-7_83 [details]
    • Meij, E., Trieschnigg, D., de Rijke, M., & Kraaij, W. (2008). Parsimonious concept modeling. In S-H. Myaeng, D. W. Oard, F. Sebastiani, T-S. Chua, & M-K. Leong (Eds.), ACM SIGIR 2008: Thirty-first Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 20-24 July 2008, Singapore: Proceedings (pp. 815-816). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1390334.1390519 [details]
    • Meij, E., Weerkamp, W., Balog, K., & de Rijke, M. (2008). Parsimonious relevance models. In S-H. Myang, D. W. Oard, F. Sebastiani, T-S. Chua, & M-K. Leong (Eds.), ACM SIGIR 2008: Thirty-first Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 20-24 July 2008, Singapore: Proceedings (pp. 817-818). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1390334.1390520 [details]
    • Snoek, C. G. M., van de Sande, K. E. A., de Rooij, O., Huurnink, B., van Gemert, J. C., Uijlings, J. R. R., He, J., Li, X., Everts, I., Nedovic, V., van Liempt, M., van Balen, R., Yan, F., Tahir, M. A., Mikolajczyk, K., Kittler, J., de Rijke, M., Geusebroek, J. M., Gevers, T., ... Koelma, D. C. (2008). The MediaMill TRECVID 2008 semantic video search engine. In TRECVID 2008: Proceedings of the 2008 TREC Video Retrieval Evaluation workshop (pp. 1-14). National Institute of Standards and Technology (NIST). http://www-nlpir.nist.gov/projects/tvpubs/tv8.papers/mediamill.pdf [details]
    • Trieschnigg, D., Meij, E., de Rijke, M., & Kraaij, W. (2008). Measuring concept relatedness using language models. In S-H. Myang, D. W. Oard, F. Sebastiani, T-S. Chua, & M-K. Leong (Eds.), ACM SIGIR 2008: Thirty-first Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 20-24 July 2008, Singapore: Proceedings (pp. 823-824). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1390334.1390523 [details]
    • Tsagkias, M., Larson, M., & de Rijke, M. (2008). Term clouds as surrogates for user generated speech. In S-H. Myaeng, D. W. Oard, F. Sebastiani, T-S. Chua, & M-K. Leong (Eds.), ACM SIGIR 2008: Thirty-first Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 20-24 July 2008, Singapore: Proceedings (pp. 773-774). Association for Computing Machinery (ACM). https://doi.org/10.1145/1390334.1390497 [details]
    • Tsagkias, M., Larson, M., Weerkamp, W., & de Rijke, M. (2008). PodCred: A framework for analyzing podcast preference. In Proceedings of the 2nd ACM Workshop on Information Credibility on the Web (WICOW 2008) (pp. 67-74). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1458527.1458545 [details]
    • Weerkamp, W., & de Rijke, M. (2008). Credibility improves topical blog post retrieval. In ACL-08: HLT: 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Proceedings of the conference (pp. 923-931). Association for Computational Linguistics (ACL). http://www.aclweb.org/anthology/P/P08/P08-1105 [details]
    • Weerkamp, W., & de Rijke, M. (2008). Looking at things differently: Exploring perspective recall for informal text retrieval. In Proceedings of the 8th Dutch-Belgian Information Retrieval Workshop (DIR 2008) (pp. 93-100). University of Maastricht. http://staff.science.uva.nl/~mdr/Publications/Files/dir2008.pdf [details]
    • Weerkamp, W., Balog, K., & de Rijke, M. (2008). Finding key bloggers, one post at a time. Frontiers in Artificial Intelligence and Applications, 178, 318-322. http://staff.science.uva.nl/~mdr/Publications/Files/ecai2008.pdf [details]

    2023

    2022

    • Heuss, M., Sarvi, F., & de Rijke, M. (2022). Fairness of Exposure in Light of Incomplete Exposure Estimation. In SIGIR '22: proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval : July 11-15, 2022, Madrid, Spain (pp. 759–769). The Association for Computing Machinery. https://doi.org/10.1145/3477495.3531977 [details]
    • Wu, C., Zhang, R., Guo, J., de Rijke, M., Fan, Y., & Cheng, X. (2022). PRADA: Practical Black-Box Adversarial Attacks against Neural Ranking Models. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2204.01321
    • ter Hoeve, M., Kiseleva, J., & de Rijke, M. (2022). Summarization with Graphical Elements. (v2 ed.) ArXiv. https://doi.org/10.48550/arXiv.2204.07551

    2021

    2020

    2019

    2018

    • Jiang, S., & de Rijke, M. (2018). Why are Sequence-to-Sequence Models So Dull? Understanding the Low-Diversity Problem of Chatbots. In A. Chuklin, J. Dalton, J. Kiseleva, A. Borisov, & M. Burtsev (Eds.), Search-Oriented Conversational AI (SCAI): EMNLP 2018 : Proceedings of the 2018 EMNLP Workshop SCAI: The 2nd International Workshop on Search-Oriented Conversational AI : October 31, 2018, Brussels, Belgium (pp. 81-86). Association for Computational Linguistics. https://doi.org/10.48550/arXiv.1809.01941, https://doi.org/10.18653/v1/W18-5712 [details]
    • Markov, I., & de Rijke, M. (2018). What Should We Teach in Information Retrieval? SIGIR Forum, 52(2), 19-30. https://doi.org/10.1145/3308774.3308780 [details]
    • Ounis, I., Allan, J., Wen, J-R., Diaz, F., de Rijke, M., Castillo, C., Chua, T-S., Donato, D., Zhang, Y., Kan, M-Y., Agarwal, D., Gao, J., Wang, J., Huang, J., Capra, R., Davison, B. R., Yilmaz, E., Liu, Y., Collins-Thompson, K., & Mei, Q. (2018). ACM SIGIR 2018 chairs' welcome. In SIGIR #41 proceedings: Ann Arbor, Michigan, USA, 08-12, July 2018 (pp. iii-iv). Association for Computing Machinery. https://doi.org/10.1145/3209978 [details]

    2017

    • Fang, H., Kamps, J., Kanoulas, E., de Rijke, M., & Yilmaz, E. (2017). Report on the 2017 ACM SIGIR International Conference Theory of Information Retrieval (ICTIR'17): conference report. SIGIR Forum, 51(3), 78-87. https://doi.org/10.1145/3190580.3190591 [details]
    • Kamps, J., Kanoulas, E., de Rijke, M., Fang, H., & Yilmaz, E. (2017). Chairs' welcome. In ICTIR'17: proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval: October 1-4, 2017, Amsterdam, the Netherlands (pp. iii). Association for Computing Machinery. https://dl.acm.org/citation.cfm?id=3121050 [details]
    • Kamps, J., Kanoulas, E., de Rijke, M., Fang, H., & Yilmaz, E. (Eds.) (2017). ICTIR'17: proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval: October 1-4, 2017, Amsterdam, the Netherlands. Association for Computing Machinery. http://dl.acm.org/citation.cfm?id=3121050 [details]
    • Nguyen, D. T., Joty, S., Boussaha, B. E. A., & de Rijke, M. (2017). Thread Reconstruction in Conversational Data using Neural Coherence Models. In Neu-IR: Workshop on Neural Information Retrieval: accepted papers ArXiv. https://arxiv.org/abs/1707.07660 [details]

    2016

    • van Dijk, D., Ren, Z., Kanoulas, E., & de Rijke, M. (2016). The University of Amsterdam (ILPS) at TREC 2015 Total Recall Track. In E. M. Voorhees, & A. Ellis (Eds.), The Twenty-Fourth Text REtrieval Conference (TREC 2015) Proceedings (NIST Special Publication; No. SP 500-321). National Institute of Standards and Technology. https://trec.nist.gov/pubs/trec24/papers/UvA.ILPS-TR.pdf [details]

    2015

    • Van Gysel, C., de Rijke, M., & Worring, M. (2015). Semantic Entities. In ESAIR’15: proceedings of the Eighth Workshop on Exploiting Semantic Annotations in Information Retrieval (pp. 1-2). Association for Computing Machinery. https://doi.org/10.1145/2810133.2810139 [details]

    2014

    • Graus, D., Odijk, D., Tsagkias, M., Weerkamp, W., & de Rijke, M. (2014). Semanticizing Search Engine Queries: The University of Amsterdam at the ERD 2014 Challenge. In ERD'14: proceedings of the First ACM International Workshop on Entity Recognition & Disambiguation: July 11, 2014, Gold Coast, Queensland, Australia (pp. 69-73). Association for Computing Machinery. https://doi.org/10.1145/2633211.2634354 [details]
    • de Rijke, M. (2014). Don't hurt them: Learning to rank from historical interaction data: (Keynote). In D. Lamas, & P. Buitelaar (Eds.), Multidisciplinary Information Retrieval: 7th Information Retrieval Facility Conference, IRFC 2014, Copenhagen, Denmark, November 10-12, 2014: proceedings (pp. xi). (Lecture Notes in Computer Science; Vol. 8849). Springer. https://doi.org/10.1007/978-3-319-12979-2 [details]
    • de Rijke, M., Kenter, T., de Vries, A. P., Zhai, C., de Jong, F., Radinsky, K., & Hofmann, K. (2014). Advances in information retrieval: 36th European Conference on IR Research, ECIR 2014, Amsterdam, The Netherlands, April 13-16, 2014: proceedings. (Lecture notes in computer science; No. 8416). Springer. https://doi.org/10.1007/978-3-319-06028-6 [details]

    2013

    • de Rooij, O., Kenter, T., & de Rijke, M. (2013). xTAS and ThemeStreams: Extendable Text Analysis Service and its Usage in a Topic Monitoring Tool. In C. Eickhoff, & A. P. de Vries (Eds.), Proceedings of the 13th Dutch-Belgian Workshop on Information Retrieval: Delft, The Netherlands, April 26th, 2013 (pp. 58-59). (CEUR Workshop Proceedings; Vol. 986). CEUR-WS. http://ceur-ws.org/Vol-986/paper_17.pdf [details]

    2012

    • Bron, M., Meij, E., Peetz, M. H., Tsagkias, M., & de Rijke, M. (2012). Team COMMIT at TREC 2011. In E. M. Voorhees, & L. P. Buckland (Eds.), The Twentieth Text REtrieval Conference Proceedings (TREC 2011) (NIST Special Publication; No. SP 500-296). National Institute of Standards and Technology. https://trec.nist.gov/pubs/trec20/t20.proceedings.html [details]
    • Huurnink, B., Berendsen, R., Hofmann, K., Meij, E., & de Rijke, M. (2012). The University of Amsterdam at the TREC 2011 Session Track. In E. M. Voorhees, & L. P. Buckland (Eds.), The Twentieth Text REtrieval Conference Proceedings (TREC 2011) (NIST Special Publication; No. SP 500-296). National Institute of Standards and Technology. https://trec.nist.gov/pubs/trec20/t20.proceedings.html [details]

    2011

    • Bekkenkamp, J., Meij, E., & de Rijke, M. (2011). Online religious studies: a pilot. In Proceedings of the ACM WebSci'11: June 14-17 2011, Koblenz, Germany Web Science Trust. http://journal.webscience.org/496/ [details]
    • Boscarino, C., Hofmann, K., Jijkoun, V., Meij, E., de Rijke, M., & Weerkamp, W. (2011). DIR 2011: Dutch_Belgian Information Retrieval Workshop Amsterdam. University of Amsterdam, Information and Language Processing group. http://edgar.meij.pro/wp-content/papercite-data/pdf/dir-2011.pdf [details]
    • Hofmann, K., Whiteson, S., & de Rijke, M. (2011). Adapting Rankers Online. In A. Hanbury, A. Rauber, & A. P. de Vries (Eds.), Multidisciplinary Information Retrieval: Second Information Retrieval Facility Conference, IRFC 2011, Vienna, Austria, June 6, 2011: proceedings (pp. 1-2). (Lecture Notes in Computer Science; Vol. 6653). Springer. https://doi.org/10.1007/978-3-642-21353-3_1 [details]

    2010

    • Agosti, M., Ferro, N., Peters, C., de Rijke, M., & Smeaton, A. (Eds.) (2010). Multilingual and Multimodal Information Access Evaluation: international conference of the Cross-Language Evaluation Forum, CLEF 2010, Padua, Italy, September 20-23, 2010 : proceedings. (Lecture Notes in Computer Science; Vol. 6360). Springer. https://doi.org/10.1007/978-3-642-15998-5 [details]
    • Bron, M., Balog, K., & de Rijke, M. (2010). Related entity finding based on co-occurrence. In E. M. Voorhees, & L. P. Buckland (Eds.), The Eighteenth Text REtrieval Conference (TREC 2009) Proceedings (NIST Special Publication; No. 500-278). National Institute of Standards and Technology. http://trec.nist.gov/pubs/trec18/papers/uamsterdam-derijke.ENT.pdf [details]
    • Bron, M., He, J., Hofmann, K., Meij, E., de Rijke, M., Tsagkias, E., & Weerkamp, W. (2010). The University of Amsterdam at TREC 2010: Session, Entity, and Relevance Feedback. In E. M. Voorhees, & L. P. Buckland (Eds.), The Nineteenth Text REtrieval Conference (TREC 2010) Proceedings (NIST Special Publication; No. 500-294). National Institute of Standards and Technology. https://trec.nist.gov/pubs/trec19/papers/univ.amsterdam.session.ent.RF.rev.pdf [details]
    • He, J., & de Rijke, M. (2010). A ranking approach to target detection for automatic link generation. In H-H. Chen, E. N. Efthimiadis, J. Savoy, F. Crestani, & S. Marchand-Millet (Eds.), SIGIR 2010: proceedings: 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval: Geneva, Switzerland, July 19-23, 2010 (pp. 831-832). Association for Computing Machinery. https://doi.org/10.1145/1835449.1835638 [details]
    • He, J., Balog, K., Hofmann, K., Meij, E., de Rijke, M., Tsagkias, M., & Weerkamp, W. (2010). Heuristic ranking and diversification of web documents. In E. M. Voorhees, & L. P. Buckland (Eds.), The Eighteenth Text REtrieval Conference (TREC 2009) Proceedings (NIST Special Publication; No. 500-278). National Institute of Standards and Technology. http://trec.nist.gov/pubs/trec18/papers/uamsterdam-derijke.WEB.pdf [details]
    • Hofmann, K., Huurnink, B., Bron, M., & de Rijke, M. (2010). Comparing click-through data to purchase decisions for retrieval evaluation. In H-H. Chen, E. N. Efthimiadis, J. Savoy, F. Crestani, & S. Marchand-Millet (Eds.), SIGIR 2010: proceedings: 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval: Geneva, Switzerland, July 19-23, 2010 (pp. 761-762). Association for Computing Machinery. https://doi.org/10.1145/1835449.1835603 [details]
    • Meij, E., & de Rijke, M. (2010). Supervised query modeling using Wikipedia. In H-H. Chen, E. N. Efthimiadis, J. Savoy, F. Crestani, & S. Marchand-Millet (Eds.), SIGIR 2010: proceedings: 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval: Geneva, Switzerland, July 19-23, 2010 (pp. 875-876). Association for Computing Machinery. https://doi.org/10.1145/1835449.1835660 [details]
    • Meij, E., Bron, M., Hollink, L., Huurnink, B., & de Rijke, M. (2010). Learning Semantic Query Suggestions. In Proceedings of the 10th Dutch-Belgian Information Retrieval Workshop (DIR 2010) (pp. 84-85). Radboud Universiteit Nijmegen, Information Foraging Lab. [details]
    • Meij, E., He, J., Weerkamp, W., & de Rijke, M. (2010). Topical diversity and relevance feedback. In E. M. Voorhees, & L. P. Buckland (Eds.), The Eighteenth Text REtrieval Conference (TREC 2009) Proceedings (NIST Special Publication; No. 500-278). National Institute of Standards and Technology. http://trec.nist.gov/pubs/trec18/papers/uamsterdam-derijke.RF.pdf [details]
    • Weerkamp, W., Tsagkias, M., & de Rijke, M. (2010). From blogs to news: identifying hot topics in the blogosphere. In E. M. Voorhees, & L. P. Buckland (Eds.), The Eighteenth Text REtrieval Conference (TREC 2009) Proceedings (NIST Special Publication; No. 500-278). National Institute of Standards and Technology. http://trec.nist.gov/pubs/trec18/papers/uamsterdam-derijke.BLOG.pdf [details]

    2009

    2008

    2011

    • Boscarino, C., Hofmann, K., Jijkoun, V., Meij, E., de Rijke, M., & Weerkamp, W. (2011). DIR 2011: the eleventh Dutch-Belgian Information Retrieval Workshop. SIGIR Forum, 45(1), 42-44. https://doi.org/10.1145/1988852.1988859 [details]
    • Clough, P., Ferro, N., Forner, P., Gonzalo, J., Huurnink, B., Kekäläinen, J., Lalmas, M., Petras, V., & de Rijke, M. (2011). CLEF 2011: Conference on Multilingual and Multimodal Information Access Evaluation. SIGIR Forum, 45(2), 32-37. https://doi.org/10.1145/2093346.2093349 [details]

    2010

    2019

    • de Rijke, M. (2019). Investeer in kennisbasis AI of word een toeschouwer. NRC Handelsblad, 8 april 2019.

    2016

    • de Rijke, M., & Graus, D. (2016). Wij zijn racisten, en daarom Google ook. NRC Handelsblad, 16. [details]

    2022

    • Lucic, A., Oosterhuis, H., Haned, H., & de Rijke, M. (2022). FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles. Poster session presented at 36th AAAI Conference on Artificial Intelligence (AAAI-2022). https://doi.org/10.48550/arXiv.1911.12199

    2021

    • Lucic, A., Srikumar, M., Bhatt, U., Xiang, A., Taly, A., Liao, Q. V., & de Rijke, M. (2021). A Multistakeholder Approach Towards Evaluating AI Transparency Mechanisms. Paper presented at HCXAI2021: ACM CHI Workshop Human-Centered Perspectives in Explainable AI, Yokohama, Japan. https://arxiv.org/abs/2103.14976 [details]

    2020

    2019

    • Pei, J., Stienstra, A., Kiseleva, Y., & de Rijke, M. (2019). SEntNet: Source-aware Recurrent Entity Network for Dialogue Response Selection. Paper presented at 4th International Workshop on Search-Oriented Conversational AI (SCAI), Macao, China. https://arxiv.org/abs/1906.06788 [details]
    • Zhang, Y., Ren, P., & de Rijke, M. (2019). Improving Background Based Conversation with Context-aware Knowledge Pre-selection. Paper presented at 4th International Workshop on Search-Oriented Conversational AI (SCAI), Macao, China. https://arxiv.org/abs/1906.06685 [details]
    • de Rijke, M. (2019). Reinforcement learning to rank. 5. Abstract from 12th ACM International Conference on Web Search and Data Mining, WSDM 2019, Melbourne, Australia. https://doi.org/10.1145/3289600.3291605 [details]

    2018

    • Joachims, T., Swaminathan, A., & de Rijke, M. (2018). Deep Learning with Logged Bandit Feedback. Paper presented at 6th International Conference on Learning Representations, ICLR 2018, Vancouver, Canada.

    2017

    • Vakulenko, S., Markov, I., & de Rijke, M. (2017). Conversational Exploratory Search via Interactive Storytelling. Paper presented at SCAI'17 — Search-Oriented Conversational AI, Amsterdam, Netherlands. https://arxiv.org/abs/1709.05298 [details]

    2015

    2012

    • Bron, M., Huurnink, B., & de Rijke, M. (2012). Linking Archives Using Document Enrichment and Term Selection. 67-68. Abstract from 12th Dutch-Belgian Information Retrieval Workshop. http://dir2012.intec.ugent.be/system/files/proceedings/DIR_2012_Proceedings.pdf
    • Meij, E. J., Weerkamp, W., & de Rijke, M. (2012). Adding Semantics to Microblog Posts (Abstract). Abstract from 12th Dutch-Belgian Information Retrieval Workshop.
    • Peetz, M. H., Meij, E. J., de Rijke, M., & Weerkamp, W. (2012). Adaptive Temporal Query Modeling (Abstract). Abstract from 12th Dutch-Belgian Information Retrieval Workshop.
    • Tsagkias, E., de Rijke, M., & Weerkamp, W. (2012). Hypergeometric Language Models for Republished Article Finding (Abstract). Abstract from 12th Dutch-Belgian Information Retrieval Workshop.
    • Weerkamp, W., Berendsen, R., Kovachev, B., Meij, E. J., Balog, K., & de Rijke, M. (2012). People Searching for People: Analysis of a People Search Engine Log (Abstract). Abstract from 12th Dutch-Belgian Information Retrieval Workshop.
    • de Rijke, M. (2012). Log File Analysis and Mining (Abstract).

    2011

    2008

    2017

    • Chuklin, A. (2017). Understanding and modeling users of modern search engines. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
    • Graus, D. P. (2017). Entities of interest: Discovery in digital traces. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
    • Kenter, T. M. (2017). Text understanding for computers. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
    • Reinanda, R. (2017). Entity associations for search. [Thesis, externally prepared, Universiteit van Amsterdam]. [details]
    • Van Gysel, C. J. H. (2017). Remedies against the vocabulary gap in information retrieval. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
    • van der Wees, M. E. (2017). What’s in a domain? Towards fine-grained adaptation for machine translation. [Thesis, fully internal, Universiteit van Amsterdam]. [details]

    2020

    2019

    2018

    2019

    • Akker, B., Markov, I. & Rijke, M. (2019). ViTOR: Learning to Rank Webpages Based on Visual Features. DANS Data Station Physical and Technical Sciences. https://doi.org/10.17026/dans-xah-fkcq
    This list of publications is extracted from the UvA-Current Research Information System. Questions? Ask the library or the Pure staff of your faculty / institute. Log in to Pure to edit your publications. Log in to Personal Page Publication Selection tool to manage the visibility of your publications on this list.
  • Ancillary activities
    • NWO
      Lid ENW-tafel Informatica
    • Springer
      Co-editor in chief The Information Retrieval Series.
edit contact information   edit profile page