A Novel Method for Detecting New Overlapping Community in Complex Evolving Networks
Document Type
Article
Publication Date
9-1-2019
Abstract
It is an important challenge to detect an overlapping community and its evolving tendency in a complex network. To our best knowledge, there is no such an overlapping community detection method that exhibits high normalized mutual information (NMI) and F-score, and can also predict an overlapping community's future considering node evolution, activeness, and multiscaling. This paper presents a novel method based on node vitality, an extension of node fitness for modeling network evolution constrained by multiscaling and preferential attachment. First, according to a node's dynamics such as link creation and destruction, we find node vitality by comparing consecutive network snapshots. Then, we combine it with the fitness function to obtain a new objective function. Next, by optimizing the objective function, we expand maximal cliques, reassign overlapping nodes, and find the overlapping community that matches not only the current network but also the future version of the network. Through experiments, we show that its NMI and F-score exceed those of the state-of-the-art methods under diverse conditions of overlaps and connection densities. We also validate the effectiveness of node vitality for modeling a node's evolution. Finally, we show how to detect an overlapping community in a real-world evolving network.
Identifier
85040621628 (Scopus)
Publication Title
IEEE Transactions on Systems Man and Cybernetics Systems
External Full Text Location
https://doi.org/10.1109/TSMC.2017.2779138
e-ISSN
21682232
ISSN
21682216
First Page
1832
Last Page
1844
Issue
9
Volume
49
Grant
17K12751
Fund Ref
Japan Society for the Promotion of Science
Recommended Citation
Cheng, Jiujun; Wu, Xiao; Zhou, Mengchu; Gao, Shangce; Huang, Zhenhua; and Liu, Cong, "A Novel Method for Detecting New Overlapping Community in Complex Evolving Networks" (2019). Faculty Publications. 7381.
https://digitalcommons.njit.edu/fac_pubs/7381
