A comparative study on community detection methods in complex networks-Reference-Cited by-同舟云学术

A comparative study on community detection methods in complex networks

Published:2018-07-27 Issue:1 Volume:35 Page:1077-1086
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Zhao Zhongying¹²,Zheng Shaoqiang¹,Li Chao¹,Sun Jinqing¹,Chang Liang³,Chiclana Francisco⁴

Affiliation:

1. College of Computer Science and Engineering, Shandong Province Key laboratory of Wisdom Mine Information Technology, Shandong University of Science and Technology, Qingdao, China

2. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

3. Guangxi Key Lab of Trusted Software, Guilin University of Electronic Technology, Guilin, China

4. Center for Computational Intelligence, Faculty of Technology, De Montfort University, Leicester, UK

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

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2. Identifying and analyzing popular phrases multi-dimensionally in social media data;Zhao;International Journal of Data Warehousing & Mining,2015

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4. A fast parallel modularity optimization algorithm (fpmqa) for community detection in on-line social network;Bu;Knowledge-Based Systems,2013

5. A novel disjoint community detection algorithm for social networks based on backbone degree and expansion;Xu;Expert Systems with Applications,2015

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