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  1. University of Computer Studies, Yangon
  2. Faculty of Computer Science

Community Detection in Social Network Using Artificial Bee Colony with Genetic Operator

http://hdl.handle.net/20.500.12678/0000004027
http://hdl.handle.net/20.500.12678/0000004027
4994971e-90bc-44c5-8182-df577530ebff
7cff9f1d-3601-41f7-bdf5-4ba005f31f54
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Publication
Title
Title Community Detection in Social Network Using Artificial Bee Colony with Genetic Operator
Language en
Publication date 2018-11-01
Authors
Aung, Thet Thet
Nyunt, Thi Thi Soe
Description
Community detection (CD) plays an important role inanalyzing social network features and helping to find outvaluable hidden information. Many research algorithmshave been proposed to find the best community in thenetwork. But it has many challenges such as scalabilityand time complexity. This paper proposes a newalgorithm, Artificial Bee Colony Algorithm with GeneticOperator (ABCGO) that combines crossover andmutation operators with Artificial Bee Colony algorithm.This paper takes modularity Q as objective function.Compared with five state-of-art algorithms, results onreal world networks reflect the effectiveness of ABCGO
Keywords
Social Network, Community Detection, Artificial Bee Colony, Modularity
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/1737
Journal articles
Second International Conference on Advanced Information Technologies (ICAIT 2018)
Conference papers
Books/reports/chapters
Thesis/dissertations
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