4 citations · 9 across the 7 of their papers we have counts for
8 papers · 1 filter
Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation
Haolun Wu, Yingxue Zhang, Chen Ma +4
To offer accurate and diverse recommendation services, recent methods use auxiliary information to foster the learning process of user and item representations. Many SOTA methods f…
Joint Multisided Exposure Fairness for Recommendation
Haolun Wu, Bhaskar Mitra, Chen Ma +2
Prior research on exposure fairness in the context of recommender systems has focused mostly on disparities in the exposure of individual or groups of items to individual users of…
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation
Chen Ma, Liheng Ma, Yingxue Zhang +3
Personalized recommender systems are playing an increasingly important role as more content and services become available and users struggle to identify what might interest them. A…
Multi-Graph Convolution Collaborative Filtering
Jianing Sun, Yingxue Zhang, Chen Ma +4
Personalized recommendation is ubiquitous, playing an important role in many online services. Substantial research has been dedicated to learning vector representations of users an…
Memory Augmented Graph Neural Networks for Sequential Recommendation
Chen Ma, Liheng Ma, Yingxue Zhang +3
The chronological order of user-item interactions can reveal time-evolving and sequential user behaviors in many recommender systems. The items that users will interact with may de…
Hierarchical Gating Networks for Sequential Recommendation
Chen Ma, Peng Kang, Xue Liu
The chronological order of user-item interactions is a key feature in many recommender systems, where the items that users will interact may largely depend on those items that user…