Truss decomposition using triangle graphs

نویسندگان

چکیده

Recent studies have shown that social networks exhibit interesting characteristics such as community structures, i.e., vertexes can be clustered into communities are densely connected together and loosely to other vertices. In order identify communities, several definitions were proposed characterize the density of connections among vertices in networks. Dense triangle cores, also known k-trusses, subgraphs which every edge participates at least \(k-2\) triangles (a clique size 3), exhibiting a high degree cohesiveness There number research works propose k-truss decomposition algorithms. However, existing in-memory algorithms for computing inefficient handling today’s massive this paper, we an efficient, yet scalable algorithm finding k-trusses large-scale network. To end, new structure, called graph speed up process prove correctness efficiency our method. We evaluate performance through extensive experiments using real-world The results comprehensive show outperform state-of-the-art methods by orders magnitudes running time.

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ژورنال

عنوان ژورنال: Soft Computing

سال: 2021

ISSN: ['1433-7479', '1432-7643']

DOI: https://doi.org/10.1007/s00500-021-06468-9