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As the size of networks increases, it is becoming important to analyze large-scale network data. A network clustering algorithm is useful for analysis of network data. Conventional network clustering algorithms in a single machine environment rather than a parallel machine environment are actively being researched. However, these algorithms cannot analyze large-scale network data because of memory size issues. As a solution, we propose a network clustering algorithm for large-scale network datadoi:10.1371/journal.pone.0203670 pmid:30303961 pmcid:PMC6179193 fatcat:5rvc225dovfgfcfyk6qkxisddy