45 citations · 80 across the 4 of their papers we have counts for
5 papers
AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment enabled by Large Language Models
Rui Zhang, Yixin Su, Bayu Distiawan Trisedya +4
The task of entity alignment between knowledge graphs (KGs) aims to identify every pair of entities from two different KGs that represent the same entity. Many machine learning-bas…
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…
Detecting Beneficial Feature Interactions for Recommender Systems
Yixin Su, Rui Zhang, Sarah Erfani +1
Feature interactions are essential for achieving high accuracy in recommender systems. Many studies take into account the interaction between every pair of features. However, this…
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…