Mingzhu Chang

CLUHCS:Dual-View Contrastive Learning Enabled Unsupervised Heterogeneous Community Search with Meta-Path Behavior Modeling

Existing community search methods heavily rely on labeled data or predefined structures, thus fail to capture obscure and dynamic community boundaries in open-world heterogeneous networks, leading to poor adaptability. They also ignore modeling behavioral patterns, resulting in poor search performan