14 citations · 35 across the 12 of their papers we have counts for
12 papers
Identifying the Hierarchical Emotional Areas in the Human Brain Through Information Fusion
Zhongyu Huang, Changde Du, Chaozhuo Li +2
The brain basis of emotion has consistently received widespread attention, attracting a large number of studies to explore this cutting-edge topic. However, the methods employed in…
Beyond Entity Alignment: Towards Complete Knowledge Graph Alignment via Entity-Relation Synergy
Xiaohan Fang, Chaozhuo Li, Yi Zhao +5
Knowledge Graph Alignment (KGA) aims to integrate knowledge from multiple sources to address the limitations of individual Knowledge Graphs (KGs) in terms of coverage and depth. Ho…
GPT4Rec: Graph Prompt Tuning for Streaming Recommendation
Peiyan Zhang, Yuchen Yan, Xi Zhang +5
In the realm of personalized recommender systems, the challenge of adapting to evolving user preferences and the continuous influx of new users and items is paramount. Conventional…
High-Frequency-aware Hierarchical Contrastive Selective Coding for Representation Learning on Text-attributed Graphs
Peiyan Zhang, Chaozhuo Li, Liying Kang +4
We investigate node representation learning on text-attributed graphs (TAGs), where nodes are associated with text information. Although recent studies on graph neural networks (GN…
ConvFormer: Revisiting Transformer for Sequential User Modeling
Hao Wang, Jianxun Lian, Mingqi Wu +5
Sequential user modeling, a critical task in personalized recommender systems, focuses on predicting the next item a user would prefer, requiring a deep understanding of user behav…
To Copy Rather Than Memorize: A Vertical Learning Paradigm for Knowledge Graph Completion
Rui Li, Xu Chen, Chaozhuo Li +8
Embedding models have shown great power in knowledge graph completion (KGC) task. By learning structural constraints for each training triple, these methods implicitly memorize int…