Search results
Results: 1,033
Number of items: 1,033
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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 -
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
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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 -
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. https://doi.org/10.1145/3411753
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Jagerman, R., Markov, I., & de Rijke, M. (2020). Safe Exploration for Optimizing Contextual Bandits. ACM Transactions on Information Systems, 38(3), Article 24. https://doi.org/10.1145/3385670
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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. https://doi.org/10.1007/s11704-018-7283-x
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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. https://doi.org/10.1145/3411754
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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
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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
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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
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