A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Structure and Dynamics of Networks: (Princeton Studies in Complexity)
The Structure and Dynamics of Networks: (Princeton Studies in Complexity)
Comparative analysis for k-means algorithms in network community detection
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
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To find the best partition of a large and complex network into a small number of communities has been addressed in many different ways In this paper, a new validity index for network partition is proposed, which is motivated by the construction of Xie-Beni index in Euclidean space The simulated annealing strategy is used to minimize this extended validity index, associating with a dissimilarity-index-based k-means iterative procedure, under the framework of a random walker Markovian dynamics on the network The proposed algorithm(SAEVI) can efficiently and automatically identify the community structure of the network and determine an appropriate number of communities without any prior knowledge about the community structure during the cooling process The computational results on several artificial and real-world networks confirm the capability of the algorithm.