COMMUNITY DETECTION IN NETWORKS USING PAGE RANK VECTORS


 


International Journal on Bioinformatics & Biosciences (IJBB)

ISSN : 1839-9614


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Paper Title;

COMMUNITY DETECTION IN NETWORKS USING PAGE RANK VECTORS


Abstract;

Nodes in the real world networks organize in the form of network communities. A community (also referred to as module or cluster)is defined as where the links are denser inside the nodes and sparser outside the nodes in the network. Communities in the networks also overlap because the nodes may belong to different clusters at once. The task of detecting communities in networks becomes an open problem because of lack of reliable algorithms. In practice all the existing community detection methods work good for nonoverlapping communities and fail to detect communities with dense overlaps. We developed a novel method for detecting communities by considering a single seed node. This method successfully captures the overlapping networks ranging from social to information and from biological to citation networks. We believe that the proposed system works well for the overlapping communities.


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https://wireilla.com/papers/ijbb/V5N4/5415ijbb01.pdf


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