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Community Detection with Self-Adapting Switching Based on Affinity
Joint Authors
Wang, Ning-Ning
Peng, Xiao-Long
Jin, Zhen
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-11-13
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Community structures in complex networks play an important role in researching network function.
Although there are various algorithms based on affinity or similarity, their drawbacks are obvious.
They perform well in strong communities, but perform poor in weak communities.
Experiments show that sometimes, community detection algorithms based on a single affinity do not work well, especially for weak communities.
So we design a self-adapting switching (SAS) algorithm, where weak communities are detected by combination of two affinities.
Compared with some state-of-the-art algorithms, the algorithm has a competitive accuracy and its time complexity is near linear.
Our algorithm also provides a new framework of combination algorithm for community detection.
Some extensive computational simulations on both artificial and real-world networks confirm the potential capability of our algorithm.
American Psychological Association (APA)
Wang, Ning-Ning& Jin, Zhen& Peng, Xiao-Long. 2019. Community Detection with Self-Adapting Switching Based on Affinity. Complexity،Vol. 2019, no. 2019, pp.1-16.
https://search.emarefa.net/detail/BIM-1132593
Modern Language Association (MLA)
Wang, Ning-Ning…[et al.]. Community Detection with Self-Adapting Switching Based on Affinity. Complexity No. 2019 (2019), pp.1-16.
https://search.emarefa.net/detail/BIM-1132593
American Medical Association (AMA)
Wang, Ning-Ning& Jin, Zhen& Peng, Xiao-Long. Community Detection with Self-Adapting Switching Based on Affinity. Complexity. 2019. Vol. 2019, no. 2019, pp.1-16.
https://search.emarefa.net/detail/BIM-1132593
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132593