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Results: 1,032
Number of items: 1,032
  • Open Access
    Wu, C. (2020). Entity-centric document understanding: Entity aspects and salience. [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
    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
    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
    ter Hoeve, M., Sim, R., Nouri, E., Fourney, A., de Rijke, M., & White, R. W. (2020). Conversations with Documents: An Exploration of Document-Centered Assistance. In CHIIR '20: proceedings of the 2020 Conference on Human Information Interaction and Retrieval : March 14-18, 2020, Vancouver, BC, Canada (pp. 43-52). The Association for Computing Machinery. https://doi.org/10.1145/3343413.3377971
  • 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
  • Akker, B. V. D., Markov, I., & Rijke, M. D. (2019). ViTOR: Learning to Rank Webpages Based on Visual Features [Data set]. DANS Data Station Physical and Technical Sciences. https://doi.org/10.17026/dans-xah-fkcq
  • Fang, Y., Zhao, X., Huang, P., Xiao, W., & de Rijke, M. (2019). M-HIN: Complex Embeddings for Heterogeneous Information Networks via Metagraphs. In SIGIR '19: proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval : July 21-25, 2019, Paris, France (pp. 913–916). The Association for Computing Machinery. https://doi.org/10.1145/3331184.3331281
  • Li, X., Chen, Y., Pettit, B., & de Rijke, M. (2019). Personalised Reranking of Paper Recommendations using Paper Content and User Behavior. ACM Transactions on Information Systems, 37(3), Article 31. https://doi.org/10.1145/3312528
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