PublisherIEEE Press. Institute of Electrical and Electronics Engineers
Rights accessOpen Access
Finding decompositions of a graph into a family of clusters is crucial to understanding its underlying structure.
While most existing approaches focus on partitioning the nodes, real-world datasets suggest the presence of overlapping communities. We present OCA, a novel algorithm to detect overlapped communities in large data graphs. It outperforms previous proposals in terms of execution time, and efficiently handles large graphs containing more than 108 nodes and edges.
CitationPadrol, A. [et al.]. Overlapping community search for social networks. A: IEEE International Conference on Data Engineering. "26th IEEE International Conference on Data Engineering". Long Beach, California: IEEE Press. Institute of Electrical and Electronics Engineers, 2010, p. 992-995.
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