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Results: 1,025
Number of items: 1,025
  • Open Access
    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
  • Open Access
    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
  • 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
  • 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. https://doi.org/10.1016/j.ipm.2017.01.005
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
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