The rapid accumulation of multi-modal data (e.g., text, images, and geo-locations) presents significant opportunities for data mining applications in healthcare and e-commerce. However, effectively retrieving such data remains challenging due to the difficulty in capturing diverse and dynamic user retrieval intents. Ex...
Tang Qian, Yifan Zhu, Lu Chen et al.· Proceedings of the 32nd ACM...· 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.
Chengyang Luo, Zi-Xing Ding, 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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