Maximal Neighbor Similarity Reveals Real Communities in Networks.

ABSTRACT: An important problem in the analysis of network data is the detection of groups of densely interconnected nodes also called modules or communities. Community structure reveals functions and organizations of networks. Currently used algorithms for community detection in large-scale real-world networks are computationally expensive or require a priori information such as the number or sizes of communities or are not able to give the same resulting partition in multiple runs. In this paper we investigate a simple and fast algorithm that uses the network structure alone and requires neither optimization of pre-defined objective function nor information about number of communities. We propose a bottom up community detection algorithm in which starting from communities consisting of adjacent pai

SUBMITTER: Zalik KR 

PROVIDER: S-EPMC4683394 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature