activity
20192026
most citedGraph-based Alignment and Uniformity for Recommendation

22 citations · 50 across the 17 of their papers we have counts for

collaborators
Showing 2023Show all

7 papers · 1 filter

cs.IR2023

Multi-view Graph Convolution for Participant Recommendation

Xiaolong Liu, Liangwei Yang, Chen Wang +3

Social networks have become essential for people's lives. The proliferation of web services further expands social networks at an unprecedented scale, leading to immeasurable comme…

cs.IR2023

Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation

Xiaolong Liu, Liangwei Yang, Zhiwei Liu +4

Personalized recommender systems aim to predict users' preferences for items. It has become an indispensable part of online services. Online social platforms enable users to form g…

cs.IR2023★ 1 cited

Unified Pretraining for Recommendation via Task Hypergraphs

Mingdai Yang, Zhiwei Liu, Liangwei Yang +4

Although pretraining has garnered significant attention and popularity in recent years, its application in graph-based recommender systems is relatively limited. It is challenging…

cs.IR2023

Knowledge Graph Context-Enhanced Diversified Recommendation

Xiaolong Liu, Liangwei Yang, Zhiwei Liu +4

The field of Recommender Systems (RecSys) has been extensively studied to enhance accuracy by leveraging users' historical interactions. Nonetheless, this persistent pursuit of acc…

cs.IR2023

Collaborative Semantic Alignment in Recommendation Systems

Chen Wang, Liangwei Yang, Zhiwei Liu +4

Traditional recommender systems primarily leverage identity-based (ID) representations for users and items, while the advent of pre-trained language models (PLMs) has introduced ri…

cs.IR2023★ 22 cited

Graph-based Alignment and Uniformity for Recommendation

Liangwei Yang, Zhiwei Liu, Chen Wang +4

Collaborative filtering-based recommender systems (RecSys) rely on learning representations for users and items to predict preferences accurately. Representation learning on the hy…

cs.IR2023★ 12 cited

Group Identification via Transitional Hypergraph Convolution with Cross-view Self-supervised Learning

Mingdai Yang, Zhiwei Liu, Liangwei Yang +4

With the proliferation of social media, a growing number of users search for and join group activities in their daily life. This develops a need for the study on the group identifi…