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An Improved Local Community Detection Algorithm Using Selection Probability
Joint Authors
Xia, Shixiong
Zhou, Yong
Zhu, Mu
Zhou, Ranran
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-12
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
In order to find the structure of local community more effectively, we propose an improved local community detection algorithm ILCDSP, which improves the node selection strategy, and sets selection probability value for every candidate node.
ILCDSP assigns nodes with different selection probability values, which are equal to the degree of the nodes to be chosen.
By this kind of strategy, the proposed algorithm can detect the local communities effectively, since it can ensure the best search direction and avoid the local optimal solution.
Various experimental results on both synthetic and real networks demonstrate that the quality of the local communities detected by our algorithm is significantly superior to the state-of-the-art methods.
American Psychological Association (APA)
Xia, Shixiong& Zhou, Ranran& Zhou, Yong& Zhu, Mu. 2014. An Improved Local Community Detection Algorithm Using Selection Probability. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-469594
Modern Language Association (MLA)
Xia, Shixiong…[et al.]. An Improved Local Community Detection Algorithm Using Selection Probability. Mathematical Problems in Engineering No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-469594
American Medical Association (AMA)
Xia, Shixiong& Zhou, Ranran& Zhou, Yong& Zhu, Mu. An Improved Local Community Detection Algorithm Using Selection Probability. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-469594
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-469594