5 papers
Scalable Similarity Search over Large Attributed Bipartite Graphs
Xi Ou, Longlong Lin, Zeli Wang +2
Bipartite graphs are widely used to model relationships between entities of different types, where nodes are divided into two disjoint sets. Similarity search, a fundamental operat…
NCSAC: Effective Neural Community Search via Attribute-augmented Conductance
Longlong Lin, Quanao Li, Miao Qiao +5
Identifying locally dense communities closely connected to the user-initiated query node is crucial for a wide range of applications. Existing approaches either solely depend on ru…
Effective and Efficient Conductance-based Community Search at Billion Scale
Longlong Lin, Yue He, Wei Chen +3
Community search is a widely studied semi-supervised graph clustering problem, retrieving a high-quality connected subgraph containing the user-specified query vertex. However, exi…
Fast Biclique Counting on Bipartite Graphs: A Node Pivot-based Approach
Xiaowei Ye, Rong-Hua Li, Longlong Lin +2
Counting the number of -bicliques (complete bipartite subgraphs) in a bipartite graph is a fundamental problem which plays a crucial role in numerous bipartite graph analys…
PSMC: Provable and Scalable Algorithms for Motif Conductance Based Graph Clustering
Longlong Lin, Tao Jia, Zeli Wang +2
Higher-order graph clustering aims to partition the graph using frequently occurring subgraphs. Motif conductance is one of the most promising higher-order graph clustering models…