93 citations · 181 across the 17 of their papers we have counts for
6 papers · 1 filter
Towards Bridging Review Sparsity in Recommendation with Textual Edge Graph Representation
Leyao Wang, Xutao Mao, Xuhui Zhan +5
Textual reviews enrich recommender systems with fine-grained preference signals and enhanced explainability. However, in real-world scenarios, users rarely leave reviews, resulting…
Augmenting Textual Generation via Topology Aware Retrieval
Yu Wang, Nedim Lipka, Ruiyi Zhang +6
Despite the impressive advancements of Large Language Models (LLMs) in generating text, they are often limited by the knowledge contained in the input and prone to producing inaccu…
Can One Embedding Fit All? A Multi-Interest Learning Paradigm Towards Improving User Interest Diversity Fairness
Yuying Zhao, Minghua Xu, Huiyuan Chen +5
Recommender systems (RSs) have gained widespread applications across various domains owing to the superior ability to capture users' interests. However, the complexity and nuanced…
Leveraging Opposite Gender Interaction Ratio as a Path towards Fairness in Online Dating Recommendations Based on User Sexual Orientation
Yuying Zhao, Yu Wang, Yi Zhang +3
Online dating platforms have gained widespread popularity as a means for individuals to seek potential romantic relationships. While recommender systems have been designed to impro…
Fairness and Diversity in Recommender Systems: A Survey
Yuying Zhao, Yu Wang, Yunchao Liu +3
Recommender systems are effective tools for mitigating information overload and have seen extensive applications across various domains. However, the single focus on utility goals…
Collaboration-Aware Graph Convolutional Network for Recommender Systems
Yu Wang, Yuying Zhao, Yi Zhang +1
Graph Neural Networks (GNNs) have been successfully adopted in recommender systems by virtue of the message-passing that implicitly captures collaborative effect. Nevertheless, mos…