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cs.SI2025
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…
cs.SI2025
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…
cs.LG2025
CoATA: Effective Co-Augmentation of Topology and Attribute for Graph Neural Networks
Tao Liu, Longlong Lin, Yunfeng Yu +4
Graph Neural Networks (GNNs) have garnered substantial attention due to their remarkable capability in learning graph representations. However, real-world graphs often exhibit subs…