Community Detection in Complex Network
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

Research Paper | Computer Science & Engineering | India | Volume 3 Issue 5, May 2014

Community Detection in Complex Network

Shikha Vishnoi

A large number of networks in nature; society and technology are defined by a mesoscopic level of organization; in which groups of nodes form tightly connected units; called communities that are sparsely inter-linked to each other. Identifying this community structure is one of the most important problems in understanding of functions and structures of real world complex systems; which is still a challenging task. Various methods proposed so far are not efficient and accurate for large networks which comprise of millions of nodes because of their high computational cost. In this manuscript we will provide the computational analysis of BGLL algorithm and overlapping community detection algorithm (OCDA) for determining the structure of complex networks. BGLL is a variant of hierarchical agglomerative clustering approach and OCDA is based on the principle of edge betweenness.

Keywords: Community structure, complex networks, BGLL, OCDA, edge betweenness

Edition: Volume 3 Issue 5, May 2014

Pages: 1326 - 1329

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How to Cite this Article?

Shikha Vishnoi, "Community Detection in Complex Network", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=20132109, Volume 3 Issue 5, May 2014, 1326 - 1329

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