Recommendation Systems

We design machine learning based models for session-based recommendation, sequential recommendation, social recommendation, POI recommendation, safe recommendation, interpretable recommendation, and so on.

  • Manal Alshehri and Xiangliang Zhang. Forgetting User Preference in Recommendation Systems with Label-Flipping. Accepted for the 2023 IEEE International Conference on Big Data, Dec 15-18, 2023 @ Sorrento, Italy (Regular Paper, 92 out of 526 submissions = 17%)
  • Ziyi Kou, Saurav Manchanda, Shih-Ting Lin, Min Xie, Haixun Wang and Xiangliang Zhang. Modeling Sequential Collaborative User Behaviors for Seller-aware Next Basket Recommendation. Accepted for publication in the CIKM 2023 proceeding. (Acceptance rate of 24%, 354 out of 1472 FULL paper submissions).
  • Zhenwei Tang, Griffin Floto, Armin Toroghi, Shichao Pei, Xiangliang Zhang and Scott Sanner. LogicRec: Recommendation with Users’ Logical Requirements. Accepted by SIGIR 2023 (Short paper, Acceptance rate = 154/613 = 25.12%)
  • Taicheng Guo, Lu Yu, Basem Shihada, Xiangliang Zhang. Few-shot News Recommendation via Cross-lingual Transfer. Accepted by The Web Conference 2023. Texas, USA on April 30 – May 4 2023. (Acceptance rate = 19.2%, 365 out of 1900 submissions)
  • Manal Abdulaziz Alshehri, Xiangliang Zhang. Generative Adversarial Zero-Shot Learning for Cold-Start News Recommendation. Accepted as a full paper by CIKM 2022.
  • Lu Yu, Shichao Pei, Feng Zhu, Longfei Li, Jun Zhou, Chuxu Zhang, Xiangliang Zhang. A Biased Sampling Method for Imbalanced Personalized Ranking. Accepted as a full paper by CIKM 2022.
  • Shijie Zhang, Hongzhi Yin, Tong Chen, Zi Huang, Lizhen Cui, and Xiangliang Zhang. Graph Embedding for Recommendation against Attribute Inference Attacks. The Web Conference 2021 (WWW’21),​ April 2021.  (acceptance rate of 20.6%, 357/1736).
  • Junliang Yu, Hongzhi Yin, Jundong Li, Qinyong Wang, Nguyen Quoc Viet Hung, and Xiangliang Zhang. Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation. The Web Conference 2021 (WWW’21), April 2021.  (acceptance rate of 20.6%, 357/1736).
  • Xuhui Ren, Hongzhi Yin, Tong Chen, Hao Wang, Nguyen Quoc Viet Hung, Zi Huang, Xiangliang Zhang. Crsal: Conversational recommender systems with adversarial learning. To appear in  ACM Transactions on Information Systems (TOIS), 2021.
  • Yujun Chen, Yuanhong Wang, Yutao Zhang, Juhua Pu,  Xiangliang Zhang. AMENDER: an Attentive and Aggregate Multi-layered Network for Dataset Recommendation. The 19th IEEE International Conference on Data Mining (ICDM 2019)  , November 8-11, 2019, Beijing, China (Short paper, Acceptance rate= 18.5%).​
  • Basmah Altaf, Lu Yu, and Xiangliang Zhang: Spatio-Temporal Attention based recurrent neural network for next poi prediction. In proceedings of IEEE Big Data 2018, Seattle, WA, USA, December 10-13, 2018 (short paper)[PDF][Bib][Slides].​
  • Lu Yu, Chuxu Zhang, Shichao Pei, Guolei Sun, Xiangliang Zhang: WalkRanker: A Unified Pairwise Ranking Model with Multiple Relations for Item Recommendation. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI 2018), pp. 2596-2603, New Orleans, February 2–7, 2018 (acceptance rate= 933/ 3800 = 24.6%)[PDF][Bib].​
  • Fuzhen Zhuang, Jing Zheng, Jingwu Chen, Xiangliang Zhang, Chuan Shi, Qing He. Transfer collaborative filtering from multiple sources via consensus regularization. In Neural Networks Volume 108, pp. 287-295, December 2018.
  • Uchenna Akujuobi, Xiangliang Zhang: Delve: A Dataset-Driven Scholarly Search and Analysis System. In SIGKDD Explorations,  Vol. 19, Issue 2, pp. 36-46, 2017 [PDF​][Bib].​