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Results: 1,033
Number of items: 1,033
  • Open Access
    Ghader, H. (2020). An empirical analysis of phrase-based and neural machine translation. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Oosterhuis, H. R. (2020). Learning from user interactions with rankings: A unification of the field. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    ter Hoeve, M., Kiseleva, Y., & de Rijke, M. (2020). What Makes a Good Summary? Reconsidering the Focus of Automatic Summarization. (v1 ed.) ArXiv. https://doi.org/https://arxiv.org/abs/2012.07619v1
  • Open Access
    Li, Z. (2020). Optimizing interactive systems with data-driven objectives. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    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
  • 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
  • Open Access
    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
  • 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
    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
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