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Scalable Community Detection using Island based Artificial Bee Colony Algorithm
http://hdl.handle.net/20.500.12678/0000004752
http://hdl.handle.net/20.500.12678/000000475263a2c4a9-1982-4dd0-91f8-675d4d0860a0
843e4de1-3605-4dbd-948d-a816211e6dbc
Publication type | ||||||
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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 |