Abstract
Community structure is an important property of networks. A number of recent studies have focused on community detection algorithms. In this paper, we propose an efficient hierarchical graph clustering algorithm based on shared neighbors and links between clusters to detect communities. The basic idea is that vertices in the same cluster should have more shared neighbors than that in different clusters. We test our method by computer generated graphs and compare it with MCL algorithm. The performance of our algorithm is quite well.
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Huijuan, Z., Shixuan, S., Yichen, C. (2013). An Efficient Hierarchical Graph Clustering Algorithm Based on Shared Neighbors and Links. In: Wang, M. (eds) Knowledge Science, Engineering and Management. KSEM 2013. Lecture Notes in Computer Science(), vol 8041. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39787-5_42
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DOI: https://doi.org/10.1007/978-3-642-39787-5_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39786-8
Online ISBN: 978-3-642-39787-5
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