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An Improved Optimization of Link-Based Label Propagation Algorithm

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Advanced Data Mining and Applications (ADMA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11323))

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Abstract

Community Detection has been an important tool for network and overlapping Community exists in real work ubiquitously. In this paper, an improved optimization of link-based label propagation algorithm rather than node called LinkLPAm is proposed to detect overlapping community. We briefly introduce our main work. Firstly, the initialization on edge labels by rough core is presented to speed up the process of detecting overlapping community, which is a big timesaver for the link network that magnified a lot of times compared with original node network. Secondly, an optimization algorithm of label propagation on link is given to update label on edge. Thirdly, in order to restrict the number of communities and the number of nodes in the community, the metric community similarity between communities is defined and greedy mergence algorithm is taken to merge communities according to community similarity. Finally, experimental result shows that our method LinkLPAm is serviceable for find reasonable overlapping community.

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Correspondence to Zhengyou Xia .

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Zhu, X., Xia, Z. (2018). An Improved Optimization of Link-Based Label Propagation Algorithm. In: Gan, G., Li, B., Li, X., Wang, S. (eds) Advanced Data Mining and Applications. ADMA 2018. Lecture Notes in Computer Science(), vol 11323. Springer, Cham. https://doi.org/10.1007/978-3-030-05090-0_42

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  • DOI: https://doi.org/10.1007/978-3-030-05090-0_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05089-4

  • Online ISBN: 978-3-030-05090-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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