Enhancing Modularity-Based Graph Clustering
نویسندگان
چکیده
Graph clustering is defined as grouping the vertices of a given input graph into clusters. This article proposes a Two-Phase Modularity-Based Graph Clustering (2-PMGC) algorithm based on modularity optimization. The algorithm consists mainly of two steps; namely, coarsening and refinement. The coarsening phase takes the original graph as input and produces levels of coarsen graphs. The second phase starts with the coarsest graph resulting from the previous phase and enhances clustering by further moving the vertices of each coarsen level between clusters. Our algorithm is evaluated for 16 real-world networks, where an obvious increase in modularity is achieved by the proposed algorithm.
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تاریخ انتشار 2013