• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Enhanced Distance Dynamics Model for Community Detection via Ego-Leader

Vol. 12, No.5, May 31, 2018
10.3837/tiis.2018.05.013 , Download Paper (Free):

Abstract

Distance dynamics model is an excellent model for uncovering the community structure of a complex network. However, the model has poor robustness. To improve the robustness, we design an enhanced distance dynamics model based on Ego-Leader and propose a corresponding community detection algorithm, called E-Attractor. The main contributions of E-Attractor are as follows. First, to get rid of sensitive parameter λ, Ego-Leader is introduced into the distance dynamics model to determine the influence of an exclusive neighbor on the distance. Second, based on top-k Ego-Leader, we design an enhanced distance dynamics model. In contrast to the traditional model, enhanced model has better robustness for all networks. Extensive experiments show that E-Attractor has good performance relative to several state-of-the-art algorithms.


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Cite this article

[IEEE Style]
Cai LiJun, Zhang Jing, Chen Lei and He TingQin, "Enhanced Distance Dynamics Model for Community Detection via Ego-Leader," KSII Transactions on Internet and Information Systems, vol. 12, no. 5, pp. 2142-2161, 2018. DOI: 10.3837/tiis.2018.05.013

[ACM Style]
LiJun, C., Jing, Z., Lei, C., and TingQin, H. 2018. Enhanced Distance Dynamics Model for Community Detection via Ego-Leader. KSII Transactions on Internet and Information Systems, 12, 5, (2018), 2142-2161. DOI: 10.3837/tiis.2018.05.013