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Scalable Community Detection using Island based Artificial Bee Colony Algorithm

http://hdl.handle.net/20.500.12678/0000004752
63a2c4a9-1982-4dd0-91f8-675d4d0860a0
843e4de1-3605-4dbd-948d-a816211e6dbc
Publication type
Article
Upload type
Publication
Title
Title Scalable Community Detection using Island based Artificial Bee Colony Algorithm
Language en
Publication date 2018-02-22
Authors
Aung, Thet Thet
Nyunt, Thi Thi Soe
Description
Many system of interest in sciences can be represented as network (social network, biological network, computer science and etc), sets of nodes joined in pairs by edges. Detecting community structure is become one of the challenging issues in the study of networked system. Community can be detected by clustering social network where nodes have more intra-community connections rather than inter-community connections. Artificial Bee Colony (ABC) algorithm is a relative new swarm intelligence base algorithm that mimics the foraging behavior of honey bee. It is fast, high efficient and doesn’t need to know the original communities number. So, it is suitable to solve complex clustering problems. ABC can also perform global search over the complex solution space. This paper proposes the large scale community detection algorithm using Island based ABC algorithm on the Spark framework and want to obtain more accurate results than in previous work has been improved.
Keywords
Artificial Bae colony, Community Detection, island model
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/490
Journal articles
Sixteenth International Conferences on Computer Applications(ICCA 2018)
Conference papers
Books/reports/chapters
Thesis/dissertations
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