Detecting Community Structure in Complex Networks Using Bacterial Chemotaxis with Fuzzy C-means Clustering

Yanling Li, Lei You, Gang Li
2014 Sensors & Transducers  
Identification of (overlapping) communities/clusters in a complex network is a general problem in data mining of network data sets. In this paper, the bacterial chemotaxis (BC) strategy is used to maximize the modularity of a network, associating with a dissimilarity-index-based and with a diffusion-distance-based fuzzy c-means clustering iterative procedure. The proposed algorithm outperforms most existing methods in the literature as regards the optimal modularity found. Experimental results
more » ... perimental results indicate that the new algorithm is efficient at detecting both good clusterings and the appropriate number of clusters.
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