Application of natural computation inspired method in community detection

• Published in: Physica A Vol. 515; pp. 130 - 150
• Main Authors: Zhang, Weitong, Zhang, Rui, Shang, Ronghua, Li, Juanfei, Jiao, Licheng
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.02.2019
• Subjects: Community detection; Community structure; Complex network; Natural computing inspired methods; Community structure; Community detection; Natural computing inspired methods; Complex network
• ISSN: 0378-4371; 1873-2119
• DOI: 10.1016/j.physa.2018.09.186

The study of community structure in complex networks has always been a subject of great concern in various fields. Community structure can reflect the dynamic characteristics and functions of complex networks. In recent years, there has been numerous methods proposed for community detection. Natural computing methods are inspired by nature Which have the ability of self-adaptation, self-organization and self-learning. This kind of methods can solve the complex problem that traditional calculation method cannot solve. With the effective network partition evaluation function proposed, the community detection problem can also be regarded as a kind of optimization problem. Therefore, natural computing methods are widely applied in community detection. This paper summarizes the application of natural computing inspired method in community detection, and briefly introduces its basic framework and development course. •This paper summarizes the application of natural computing inspired method in community detection.•We give a detailed overview of several situations of complex network structure.•We summarize the community structure in complex network and the evaluation index of its partition results.•We introduce the basic framework of the heuristic method of natural computing.