{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T09:27:54Z","timestamp":1766050074490,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,7,31]],"date-time":"2022-07-31T00:00:00Z","timestamp":1659225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico","award":["13869.22-P","13541.22-P","PRODEP"],"award-info":[{"award-number":["13869.22-P","13541.22-P","PRODEP"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Axioms"],"abstract":"<jats:p>A hybrid variant of the Fuzzy C-Means and K-Means algorithms is proposed to solve large datasets such as those presented in Big Data. The Fuzzy C-Means algorithm is sensitive to the initial values of the membership matrix. Therefore, a special configuration of the matrix can accelerate the convergence of the algorithm. In this sense, a new approach is proposed, which we call Hybrid OK-Means Fuzzy C-Means (HOFCM), and it optimizes the values of the membership matrix parameter. This approach consists of three steps: (a) generate a set of n solutions of an x dataset, applying a variant of the K-Means algorithm; (b) select the best solution as the basis for generating the optimized membership matrix; (c) resolve the x dataset with Fuzzy C-Means. The experimental results with four real datasets and one synthetic dataset show that HOFCM reduces the time by up to 93.94% compared to the average time of the standard Fuzzy C-Means. It is highlighted that the quality of the solution was reduced by 2.51% in the worst case.<\/jats:p>","DOI":"10.3390\/axioms11080377","type":"journal-article","created":{"date-parts":[[2022,7,31]],"date-time":"2022-07-31T21:49:02Z","timestamp":1659304142000},"page":"377","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Hybrid Fuzzy C-Means Clustering Algorithm Oriented to Big Data Realms"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5138-7984","authenticated-orcid":false,"given":"Joaqu\u00edn","family":"P\u00e9rez-Ortega","sequence":"first","affiliation":[{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico\/Cenidet, Cuernavaca 62490, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6597-8427","authenticated-orcid":false,"given":"Sandra Silvia","family":"Roblero-Aguilar","sequence":"additional","affiliation":[{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico\/Cenidet, Cuernavaca 62490, Mexico"},{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico\/IT Tlalnepantla, Tlalnepantla 54070, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nelva Nely","family":"Almanza-Ortega","sequence":"additional","affiliation":[{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico\/IT Tlalnepantla, Tlalnepantla 54070, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9307-0734","authenticated-orcid":false,"given":"Juan","family":"Frausto Sol\u00eds","sequence":"additional","affiliation":[{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico\/IT Cd. Madero, Madero 89440, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Crisp\u00edn","family":"Zavala-D\u00edaz","sequence":"additional","affiliation":[{"name":"Faculty of Accounting, Administration and Informatic, Universidad Aut\u00f3noma del Estado de Morelos, Cuernavaca 62209, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8842-0899","authenticated-orcid":false,"given":"Yasm\u00edn","family":"Hern\u00e1ndez","sequence":"additional","affiliation":[{"name":"Tecnol\u00f3gico Nacional de M\u00e9xico\/Cenidet, Cuernavaca 62490, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vanesa","family":"Landero-N\u00e1jera","sequence":"additional","affiliation":[{"name":"Computer Systems, Universidad Polit\u00e9cnica de Apodaca, Apodaca 66600, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0895-7177(93)90202-A","article-title":"A survey of fuzzy clustering","volume":"18","author":"Yang","year":"1993","journal-title":"Math. 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