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Community Discovery Algorithm Based on Clustering and Genetic Optimization

Befikadu Birtukan Sieyum

Abstract: Community discovery algorithm is recently active area of scientific research and a study of in real world networks such as, computer network, social networks. Social network is a complex network of includes community groups, that have relationship between people in common identity, location, interests, occupations etc. It is used to have better standard community structure in complex network. This study proposed that a combination of clustering which is specified in k-means algorithm and genetic algorithm. In community discovery research area, there are many methods to solve a problem, because of this article depends on overlapping community study used the clique percolation method (CPM) to add in both algorithm that gives a better result in previous works. The study improves to have well structure community; quality of the relationship between two nodes satisfied and accurate relationship between each network in community.

Keywords: Community discovery, Clustering algorithm, Genetic optimization, k means clustering

Country: China, Subject Area: Computer Engineering

Pages: 1878 - 1882

Edition: Volume 8 Issue 5, May 2019

How to Cite this Article?

Befikadu Birtukan Sieyum, "Community Discovery Algorithm Based on Clustering and Genetic Optimization", International Journal of Science and Research (IJSR), https://www.ijsr.net/archive/v8i5/show_abstract.php?id=ART20198308, Volume 8 Issue 5, May 2019, 1878 - 1882

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