Efficient Truss Computation for Large Hypergraphs

Xinzhou Wang, Yinjia Chen, Zhiwei Zhang*, Peng Peng Qiao, Guoren Wang

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

Cohesive subgraph mining has been applied in many areas, including social networks, cooperation networks, and biological networks. The k-truss of a graph is the maximal subgraph in which each edge is contained in at least k triangles. Existing k-truss models are defined solely in pairwise graphs and are hence unsuitable for hypergraphs. In this paper, we propose a novel problem, named (k, α, β) -truss computation in hypergraphs. We then propose two hypergraph conversions. The first converts a hypergraph into a pairwise graph, while the second converts it into a projected graph. We further propose two algorithms for computing (k, α, β) -truss in hypergraphs based on these two types of conversions. Experiments show that our (k, α, β) -truss model is effective and our algorithms are efficient in large hypergraphs.

源语言英语
主期刊名Web Information Systems Engineering – WISE 2022 - 23rd International Conference, Proceedings
编辑Richard Chbeir, Helen Huang, Fabrizio Silvestri, Yannis Manolopoulos, Yanchun Zhang, Yanchun Zhang
出版商Springer Science and Business Media Deutschland GmbH
290-305
页数16
ISBN(印刷版)9783031208904
DOI
出版状态已出版 - 2022
活动23rd International Conference on Web Information Systems Engineering, WISE 2021 - Biarritz, 法国
期限: 1 11月 20223 11月 2022

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
13724 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议23rd International Conference on Web Information Systems Engineering, WISE 2021
国家/地区法国
Biarritz
时期1/11/223/11/22

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