Detecting overlapping communities of weighted networks via a local algorithm |
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Authors: | Duanbing Chen Zehua Lv Yan Fu |
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Institution: | a Web Sciences Center, School of Computer Science, University of Electronic Science and Technology of China, Chengdu 611731, PR China b School of Computer Science, Huazhong University of Science and Technology, Wuhan 430074, PR China |
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Abstract: | Identification of communities is significant in understanding the structures and functions of networks. Since some nodes naturally belong to several communities, the study of overlapping communities has attracted increasing attention recently, and many algorithms have been designed to detect overlapping communities. In this paper, an overlapping communities detecting algorithm is proposed whose main strategies are finding an initial partial community from a node with maximal node strength and adding tight nodes to expand the partial community. Seven real-world complex networks and one synthetic network are used to evaluate the algorithm. Experimental results demonstrate that the algorithm proposed is efficient for detecting overlapping communities in weighted networks. |
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Keywords: | Weighted networks Overlapping community Local algorithm Node strength |
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