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Results: 10
Number of items: 10
  • Open Access
    Fang, Y., Zhao, X., Chen, Y., Xiao, W., & De Rijke, M. (2023). PF-HIN: Pre-Training for Heterogeneous Information Networks. IEEE Transactions on Knowledge and Data Engineering, 35(8), 8372-8385. https://doi.org/10.1109/TKDE.2022.3206597
  • Chen, Y., Wang, Y., Ren, P., Wang, M., & de Rijke, M. (2022). Bayesian Feature Interaction Selection for Factorization Machines. Artificial Intelligence, 302, Article 103589. https://doi.org/10.1016/j.artint.2021.103589
  • 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
  • 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
  • Open Access
    Zou, J., Chen, Y., & Kanoulas, E. (2020). Towards Question-based Recommender Systems. 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. 881-890). Association for Computing Machinery. https://doi.org/10.1145/3397271.3401180
  • 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
  • Chen, Y., Ren, P., Wang, Y., & de Rijke, M. (2019). Bayesian personalized feature interaction selection for factorization machines. 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. 665-674). The Association for Computing Machinery. https://doi.org/10.1145/3331184.3331196
  • Open Access
    Chen, Y. (2019). Learning for top-N recommendations: High-dimensional and heterogeneous information. [Thesis, fully internal, Universiteit van Amsterdam].
  • Chen, Y., & de Rijke, M. (2018). A Collective Variational Autoencoder for Top-N Recommendation with Side Information. In Proceedings of the 3rd Workshop on Deep Learning for Recommender Systems: In conjunction with RecSys 2018 : October 06, 2018, Vancouver, Canada (pp. 3-9). (ICPS). ACM. https://doi.org/10.1145/3270323.3270326
  • Chen, Y., Zhao, X., & de Rijke, M. (2017). Top-N Recommendation with High-dimensional Side Information via Locality Preserving Projection. In SIGIR'17 : proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval: August 7-11, 2017, Shinjuku, Tokyo, Japan (pp. 985-988). Association for Computing Machinery. https://doi.org/10.1145/3077136.3080697
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