A Fast Overlapping Community Detection Algorithm with Self-Correcting Ability
Joint Authors
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-13
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Due to the defects of all kinds of modularity, thispaper defines a weighted modularity based on the densityand cohesion as the new evaluation measurement.
Since the proportion of the overlapping nodes in network is very low, the number of the nodes’ repeat visits can be reduced by signing the vertices with the overlapping attributes.
In this paper, we propose three testconditions for overlapping nodes and present a fast overlappingcommunity detection algorithm with self-correctingability, which is decomposed into two processes.
Under thecontrol of overlapping properties, the complexity of thealgorithm tends to be approximate linear.
And we also givea new understanding on membership vector.
Moreover, weimprove the bridgeness function which evaluates the extentof overlapping nodes.
Finally, we conduct the experimentson three networks with well known community structuresand the results verify the feasibility and effectiveness of ouralgorithm.
American Psychological Association (APA)
Cui, Laizhong& Qin, Lei& Lu, Nan. 2014. A Fast Overlapping Community Detection Algorithm with Self-Correcting Ability. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1050841
Modern Language Association (MLA)
Cui, Laizhong…[et al.]. A Fast Overlapping Community Detection Algorithm with Self-Correcting Ability. The Scientific World Journal No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-1050841
American Medical Association (AMA)
Cui, Laizhong& Qin, Lei& Lu, Nan. A Fast Overlapping Community Detection Algorithm with Self-Correcting Ability. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-1050841
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1050841