24 citations · 85 across the 13 of their papers we have counts for
14 papers
GraSP: Simple yet Effective Graph Similarity Predictions
Haoran Zheng, Jieming Shi, Renchi Yang
Graph similarity computation (GSC) is to calculate the similarity between one pair of graphs, which is a fundamental problem with fruitful applications in the graph community. In G…
A Versatile Framework for Attributed Network Clustering via K-Nearest Neighbor Augmentation
Yiran Li, Gongyao Guo, Jieming Shi +4
Attributed networks containing entity-specific information in node attributes are ubiquitous in modeling social networks, e-commerce, bioinformatics, etc. Their inherent network to…
Effective Clustering on Large Attributed Bipartite Graphs
Renchi Yang, Yidu Wu, Xiaoyang Lin +3
Attributed bipartite graphs (ABGs) are an expressive data model for describing the interactions between two sets of heterogeneous nodes that are associated with rich attributes, su…
SlotGAT: Slot-based Message Passing for Heterogeneous Graph Neural Network
Ziang Zhou, Jieming Shi, Renchi Yang +2
Heterogeneous graphs are ubiquitous to model complex data. There are urgent needs on powerful heterogeneous graph neural networks to effectively support important applications. We…
Efficient High-Quality Clustering for Large Bipartite Graphs
Renchi Yang, Jieming Shi
A bipartite graph contains inter-set edges between two disjoint vertex sets, and is widely used to model real-world data, such as user-item purchase records, author-article publica…
Crowdsourcing Fraud Detection over Heterogeneous Temporal MMMA Graph
Zequan Xu, Qihang Sun, Shaofeng Hu +2
The rise of the click farm business using Multi-purpose Messaging Mobile Apps (MMMAs) tempts cybercriminals to perpetrate crowdsourcing frauds that cause financial losses to click…