Community search (CS) is a fundamental problem in graph analysis, which aims to identify a query-dependent cohesive subgraph that satisfies a specific community model and contains the given query vertices. While numerous CS approaches have been proposed, including non-learning-based and learning-based ones, existing re...
Yu-Han Zhou, Zheng Wu, Qing Liu et al.· Proceedings of the ACM on Ma...· 0 citations
An adaptive community search framework ECHO is proposed, which consistently outperforms state-of-the-art methods in terms of community quality while achieving superior search efficiency.
Cheng-Yang Luo, Zi-Xing Ding, Qing Liu et al.· Proceedings of the 32nd ACM...· 0 citations
A hybrid propagation model that jointly captures layer-specific diffusion dynamics and probabilistic cross-layer propagation is introduced that formally defines the Mlim problem and establishes its NP-hardness, monotonicity, and submodularity.
Xueqin Chang, Rui-Ze Liu, Qing Liu et al.· Proceedings of the 32nd ACM...· 0 citations
In this paper, for the first time, we study the community search problem over multimodal graphs. This task aims to identify a query vertex-containing subgraph that is both structurally cohesive and semantically coherent with multimodal query inputs (e.g., text and images). Existing community search methods fail to capt...
Chengyang Luo, Zi-Xing Ding, Qing Liu et al.· Proceedings of the 32nd ACM...· 0 citations
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