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Results: 1,032
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    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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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
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