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Scalable Community Detection using Island based Artificial Bee Colony Algorithm

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dc.contributor.author Aung, Thet Thet
dc.contributor.author Nyunt, Thi Thi Soe
dc.date.accessioned 2019-07-04T06:42:14Z
dc.date.available 2019-07-04T06:42:14Z
dc.date.issued 2018-02-22
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/490
dc.description.abstract 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. en_US
dc.language.iso en en_US
dc.publisher Sixteenth International Conferences on Computer Applications(ICCA 2018) en_US
dc.subject Artificial Bae colony en_US
dc.subject Community Detection en_US
dc.subject island model en_US
dc.title Scalable Community Detection using Island based Artificial Bee Colony Algorithm en_US
dc.type Article en_US

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