Abstract
Real-world networks naturally contain a lot of communities. Identifying the community structures is a crucial endeavor to analyze the networks. Here, we propose a novel algorithm which finds the community structures from seed expansion. Its expansion process bases on the transmissive probabilities coming from seed vertices and the modularity Q function which is firstly defined by Newman et al.. The experimental evaluation is conducted on real-world networks. The evaluation shows that our algorithm has good results in quality.
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Wei, F., Qian, W., Fei, Z., Zhou, A. (2010). Identifying Community Structures in Networks with Seed Expansion. In: Kitagawa, H., Ishikawa, Y., Li, Q., Watanabe, C. (eds) Database Systems for Advanced Applications. DASFAA 2010. Lecture Notes in Computer Science, vol 5981. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12026-8_47
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DOI: https://doi.org/10.1007/978-3-642-12026-8_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12025-1
Online ISBN: 978-3-642-12026-8
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