57 citations · 106 across the 17 of their papers we have counts for
5 papers · 1 filter
Edge-Enhanced Global Disentangled Graph Neural Network for Sequential Recommendation
Yunyi Li, Pengpeng Zhao, Guanfeng Liu +4
Sequential recommendation has been a widely popular topic of recommender systems. Existing works have contributed to enhancing the prediction ability of sequential recommendation s…
Quaternion-Based Graph Convolution Network for Recommendation
Yaxing Fang, Pengpeng Zhao, Guanfeng Liu +4
Graph Convolution Network (GCN) has been widely applied in recommender systems for its representation learning capability on user and item embeddings. However, GCN is vulnerable to…
A Unified Framework for Cross-Domain and Cross-System Recommendations
Feng Zhu, Yan Wang, Jun Zhou +3
Cross-Domain Recommendation (CDR) and Cross-System Recommendation (CSR) have been proposed to improve the recommendation accuracy in a target dataset (domain/system) with the help…
Social Group Query Based on Multi-fuzzy-constrained Strong Simulation
Guliu Liu, Lei Li, Guanfeng Liu +1
Traditional social group analysis mostly uses interaction models, event models, or other methods to identify and distinguish groups. This type of method can divide social participa…
Cross-Domain Recommendation: Challenges, Progress, and Prospects
Feng Zhu, Yan Wang, Chaochao Chen +3
To address the long-standing data sparsity problem in recommender systems (RSs), cross-domain recommendation (CDR) has been proposed to leverage the relatively richer information f…