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Results: 1,025
Number of items: 1,025
  • Open Access
    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
  • Open Access
    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
  • Open Access
    Jagerman, R. M. (2020). Efficient, safe and adaptive learning from user interactions. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    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
  • Open Access
    Ma, M., Ren, P., Chen, Z., Ren, Z., Zhao, L., Ma, J., & de Rijke, M. (2020). Mixed Information Flow for Cross-domain Sequential Recommendations. (v3 ed.) ArXiv. https://doi.org/10.48550/arXiv.2012.00485
  • Open Access
    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
  • Open Access
    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. https://doi.org/10.1016/j.ipm.2020.102215
  • Open Access
    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
  • Open Access
    Jiang, S., Wolf, T., Monz, C., & de Rijke, M. (2020). TLDR: Token Loss Dynamic Reweighting for Reducing Repetitive Utterance. (v2 ed.) ArXiv. https://doi.org/10.48550/arXiv.2003.11963
  • Open Access
    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
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