Enhanced Distance Dynamics Model for Community Detection via Ego-Leader

• Cai LiJun,
• Zhang Jing,
• Chen Lei,
• He TingQin,

Vol. 12, No. 5, May 30, 2018
10.3837/tiis.2018.05.013 , Download Paper (Free):

• community detection
• interaction model
• complex network
• Ego Network
• Leader

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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