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Essentially, the concept is founded on the theory that the structure of a community may be thought of as a high-density node surrounded by neighbors of minor densities and that community centers are located at a significant distance from one another. We propose a concept termed \u201ccommunity centrality\u201d based on finding motifs to measure the probability of a node becoming the community center in a setting like this and then disseminate multiple, substantial center probabilities all over the network through a node closeness score mechanism. The experimental results show that the proposed method is more efficient than many other already used methods.<\/jats:p>","DOI":"10.3233\/jifs-220224","type":"journal-article","created":{"date-parts":[[2022,12,9]],"date-time":"2022-12-09T10:07:19Z","timestamp":1670580439000},"page":"6911-6924","source":"Crossref","is-referenced-by-count":1,"title":["Density and node closeness based clustering method for community detection"],"prefix":"10.1177","volume":"44","author":[{"given":"Imam","family":"Yagoub","sequence":"first","affiliation":[{"name":"School of Computer and Artificial Intelligence, Zhengzhou University, 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhengzheng","family":"Lou","sequence":"additional","affiliation":[{"name":"School of Computer and Artificial Intelligence, Zhengzhou University, 450001, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baozhi","family":"Qiu","sequence":"additional","affiliation":[{"name":"School 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