Trust-Oriented Data Analytics in Online Social Networks

Research output

Research output per year 2023 2023 2024 2025

• 6 Conference proceeding contribution
• 3 Article
• 1 Editorial

Research output per year

Research output per year

Search results

• 2025

  Few-shot causal representation learning for out-of-distribution generalization on heterogeneous graphs

  Ding, P., Wang, Y., Liu, G., Wang, N. & Zhou, X., Apr 2025, In: IEEE Transactions on Knowledge and Data Engineering. 37, 4, p. 1804-1818 15 p.

  Research output: Contribution to journal › Article › peer-review
  1 Citation (Scopus)
• 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 Access

  File
  3 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)

• Trustworthy recommender systems

  Wang, S., Zhang, X., Wang, Y. & Ricci, F., Aug 2024, In: ACM Transactions on Intelligent Systems and Technology. 15, 4, p. 1-20 20 p., 84.

  Research output: Contribution to journal › Article › peer-review

  Open Access
  34 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

  • Graph 100%
  • Node 27%
  • Neural Networks 22%
  • Module 20%
  • Scenarios 18%
  2 Citations (Scopus)

• Data science for next-generation recommender systems

  Wang, S., Wang, Y., Sivrikaya, F., Albayrak, S. & Anelli, V. W., Aug 2023, In: International Journal of Data Science and Analytics. 16, 2, p. 135-145 11 p.

  Research output: Contribution to journal › Editorial › peer-review

  • Recommender Systems 100%
  • Data Science 81%
  • Recommender systems 60%
  • Machine Learning 28%
  • Machine learning 18%
  17 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

  • Experiments 100%
  17 Citations (Scopus)

• Few-shot semantic relation prediction across heterogeneous graphs

  Ding, P., Wang, Y., Liu, G. & Zhou, X., Oct 2023, In: IEEE Transactions on Knowledge and Data Engineering. 35, 10, p. 10265-10280 16 p.

  Research output: Contribution to journal › Article › peer-review

  • Semantics 100%
  • Prediction 93%
  • Graph in graph theory 53%
  • Labeled data 41%
  • Neural Networks 32%
  3 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 Access

  • Recommender systems 100%
  • Sampling 23%
  • Experiments 11%
  1 Citation (Scopus)