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ICSES Transactions on Data Science, Engineering and Technology
Vol. 3, No. 1, Mar. 2020


Complex Networks, Communities and Fuzzy Structures

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a Beijing University of Posts and Telecommunications, Beijing, China
b Central University of Finance and Economics, Beijing, China

 

Highlights and Novelties
1- The most important issues on community detection problem were reviewed, including the properties of community structure in complex networks.

2- An important type of communities, i.e. the fuzzy communities and the applications and challenges of community detection works.

3- After these explanations of the nature of the community structure in complex network, we can have a clear landscape of the growth of community detection technology.

 

Manuscript Abstract
Community detection has many potential applications from Computer Science to Biology. The main purpose of community detection is to unveil the community structure of the network. Having the community structure, one can understand the functional properties of the network. In this paper, the most important issues on community detection problem were reviewed, including the properties of community structure in complex networks, an important type of communities, i.e. the fuzzy communities and the applications and challenges of community detection works. After these explanations of the nature of the community structure in complex network, we can have a clear landscape of the growth of community detection technology.On the other hand, the quality measures are used where the true communities are not available and they estimate how much a partition is meaningful with respect to other partitions. Finally, in order to compare the performance of the algorithms, one needs to test them on some benchmark graph. So far, only few benchmark networks have been proposed for evaluating community detection methods. The most prevalent one are the GN, the LFR, and the ring of cliques benchmark graphs.

 

Keywords
 Complex networks   Community structure   Fuzzy communities   Signed networks 

 

Copyright and Licence
© Copyright was transferred to International Computer Science and Engineering Society (ICSES) by all the Authors. This manuscript is published in Open-Access manner based on the copyright licence of Creative Commons Attribution Non Commercial 4.0 International (CC BY-NC 4.0).

 

Cite this manuscript as
Hui-Jia Li, Hui-Dong Wu, "Complex Networks, Communities and Fuzzy Structures," ICSES Transactions on Data Science, Engineering and Technology, vol. 3, no. 1, pp. 1-4, Mar. 2020.

 

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Manuscript ID: 324
Pages: 1-4
Submitted: 2020-03-14
Accepted: 2020-03-22
Published: 2020-03-30


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Journal

ICSES Transactions on Data Science, Engineering and Technology
ISSN: 2467-297X

ISSN: 2467-297X
Frequency: Quarterly
Accessability: Online - Open Access (till 2020)
Founded in: Feb. 2018
Publisher: ICSES
DOI Suffix: 10.31424/icses.itdset