CLOSE: Local Community Detection by LOcal Structure Expansion in a Complex Network

Zhi Jia Jian, Hao Shang Ma, Jen Wei Huang

研究成果: Conference contribution

2 引文 斯高帕斯(Scopus)

摘要

There have been more and more researches on community discovery in complex networks. Expanding of a source node into a community is one of the most successful methods for local community detection, especially when the global structure of the network is not accessible. In this paper, we propose CLOSE algorithm, Local Community Detection by LOcal Structure Expansion, based on the local expansion technique in the community detection. In CLOSE, we propose a novel connective function to identify a better source node. The node is in the center of a highly connected component of a graph. CLOSE selects a group of nodes instead of a single node to be the seed for the expansion of a local community. In addition, using the neighboring group can identify a suitable community for a hub node. Moreover, the expansion strategy is based on the label propagation technique instead of local community measurements. In experiments, we compare the performance of CLOSE with previous methods both on synthetic networks from the LFR Benchmark and real-world networks. We also examine the merit of the source node selection strategy. Both source node selection and community detection in CLOSE outperform previous algorithms.

原文English
主出版物標題Proceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781728146669
DOIs
出版狀態Published - 2019 十一月
事件24th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019 - Kaohsiung, Taiwan
持續時間: 2019 十一月 212019 十一月 23

出版系列

名字Proceedings - 2019 International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019

Conference

Conference24th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2019
國家/地區Taiwan
城市Kaohsiung
期間19-11-2119-11-23

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦科學應用
  • 人機介面

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