Research output per year
Research output per year
Search results
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2024
A hierarchical and disentangling interest learning framework for unbiased and true news recommendation
Wang, S., Wang, W., Zhang, X., Wang, Y., Liu, H. & Chen, F., 2024, KDD'24: proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY: Association for Computing Machinery, p. 3200-3211 12 p. (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining).Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
Open AccessFile3 Citations (Scopus)1 Downloads (Pure) -
Large language models for intent-driven session recommendations
Sun, Z., Liu, H., Qu, X., Feng, K., Wang, Y. & Ong, Y-S., 2024, SIGIR'24: proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval. New York, NY: Association for Computing Machinery (ACM), p. 324-334 11 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
10 Citations (Scopus) -
Update: mining user-news engagement patterns for dual-target cross-domain fake news detection
Yang, X., Wang, Y., Zhang, X., Wang, S., Wang, H. & Lam, K-Y., 2024, DSAA 2024: 2024 IEEE 11th International Conference on Data Science and Advanced Analytics. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), p. 574-583 10 p. ( IEEE International Conference on Data Science and Advanced Analytics).Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
2 Citations (Scopus) -
2023
Cross-heterogeneity graph few-shot learning
Ding, P., Wang, Y. & Liu, G., 2023, CIKM '23: proceedings of the 32nd ACM International Conference on Information and Knowledge Management. Piscataway, NJ: Association for Computing Machinery, Inc, p. 420-429 10 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
2 Citations (Scopus) -
Domain disentanglement with interpolative data augmentation for dual-target cross-domain recommendation
Zhu, J., Wang, Y., Zhu, F. & Sun, Z., 2023, Proceedings of the Seventeenth ACM Conference on Recommender Systems. New York: Association for Computing Machinery, p. 515-527 13 p.Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
17 Citations (Scopus) -
Theoretically guaranteed bidirectional data rectification for robust sequential recommendation
Sun, Y., Yang, X., Sun, Z., Wang, B. & Wang, Y., 2023, 37th Conference on Neural Information Processing Systems (NeurIPS 2023). Oh, A., Naumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). San Diego, CA: Neural Information Processing Systems (NIPS) Foundation, p. 1-13 13 p. (Advances in Neural Information Processing Systems; vol. 36).Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review
Open Access1 Citation (Scopus)