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Communication Dans Un Congrès Année : 2022

Quasi-Clique Mining for Graph Summarization

Résumé

Several graph summarization approaches aggregate dense sub-graphs into super-nodes leading to a compact summary of the input graph. The main issue for these approaches is how to achieve a high compression rate while retaining as much information as possible about the original graph structure within the summary. These approaches necessarily involve an algorithm to mine dense structures in the graph such as quasi-clique enumeration algorithms. In this paper, we focus on improving these mining algorithms for the specific task of graph summarization. We first introduce a new pre-processing technique to speed up this mining step. Then, we extend existing quasi-clique enumeration algorithms with this filtering technique and apply them to graph summarization.
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Dates et versions

hal-03762142 , version 1 (02-03-2023)

Identifiants

Citer

Antoine Castillon, Julien Baste, Hamida Seba, Mohammed Haddad. Quasi-Clique Mining for Graph Summarization. Database and Expert Systems Applications. DEXA 2022, Aug 2022, Vienne, Austria. pp.310-315, ⟨10.1007/978-3-031-12426-6_29⟩. ⟨hal-03762142⟩
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