Lightweight Support Vector Clustering Algorithm for Community Detection in Complex Networks

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

The community structure is one of the most attractive properties of a complex network. This structure has been fundamental to advancements in various scientific branches. Numerous tools that involve community detection algorithms have been used in recent studies. In this paper, we propose a lightweight support vector clustering method. It surpasses traditional support vector approaches in terms of accuracy and complexity on account of its innovative design of distance calculations and the utilization of stable equilibrium points in the community assignment process. Extensive experiments are undertaken in computer-generated networks as well as real-world datasets. The results illustrate the competitive performance of the proposed algorithm compared to its community detection counterparts.

源语言英语
主期刊名Proceedings of the 37th Chinese Control Conference, CCC 2018
编辑Xin Chen, Qianchuan Zhao
出版商IEEE Computer Society
2317-2322
页数6
ISBN(电子版)9789881563941
DOI
出版状态已出版 - 5 10月 2018
活动37th Chinese Control Conference, CCC 2018 - Wuhan, 中国
期限: 25 7月 201827 7月 2018

出版系列

姓名Chinese Control Conference, CCC
2018-July
ISSN(印刷版)1934-1768
ISSN(电子版)2161-2927

会议

会议37th Chinese Control Conference, CCC 2018
国家/地区中国
Wuhan
时期25/07/1827/07/18

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