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A Graph-theoretic Framework for Multi-layered k-community Clique Relaxation

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dc.contributor.author Khaing, Soe Soe
dc.contributor.author Yin, Zin Mar
dc.date.accessioned 2019-07-11T04:14:10Z
dc.date.available 2019-07-11T04:14:10Z
dc.date.issued 2013-02-26
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/710
dc.description.abstract In network-based data mining, clique percolation brings an attractive feature for finding communities in a graph as well as the overlapping areas of these communities. Despite complete clique formalization, some of the properties of clique structure have been relaxed to investigate more effective and efficient manners to identify the community structure in large and sparse network. In this paper, it is proposed the idea that how to take advantages of the clique relaxation concept of k-community, introduced by Verma and Butenko (2013), with some modifications in clustering cohesive groups. In addition, we intend to promote the quality of the cluster by means of new multi-layered consideration. en_US
dc.language.iso en en_US
dc.publisher Eleventh International Conference On Computer Applications (ICCA 2013) en_US
dc.subject finding community en_US
dc.subject clique percolation en_US
dc.subject clique relaxation en_US
dc.subject k-community en_US
dc.title A Graph-theoretic Framework for Multi-layered k-community Clique Relaxation en_US
dc.type Article en_US

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