485 citations · 1.5k across the 72 of their papers we have counts for
4 papers · 1 filter
Intrinsic and Extrinsic Factor Disentanglement for Recommendation in Various Context Scenarios
Yixin Su, Wei Jiang, Fangquan Lin +6
In recommender systems, the patterns of user behaviors (e.g., purchase, click) may vary greatly in different contexts (e.g., time and location). This is because user behavior is jo…
Detecting Arbitrary Order Beneficial Feature Interactions for Recommender Systems
Yixin Su, Yunxiang Zhao, Sarah Erfani +2
Detecting beneficial feature interactions is essential in recommender systems, and existing approaches achieve this by examining all the possible feature interactions. However, the…
Neural Graph Matching based Collaborative Filtering
Yixin Su, Rui Zhang, Sarah Erfani +1
User and item attributes are essential side-information; their interactions (i.e., their co-occurrence in the sample data) can significantly enhance prediction accuracy in various…
MMF: Attribute Interpretable Collaborative Filtering
Yixin Su, Sarah Monazam Erfani, Rui Zhang
Collaborative filtering is one of the most popular techniques in designing recommendation systems, and its most representative model, matrix factorization, has been wildly used by…