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   <dc:title>Fuzzy measures: a solution to deal with community detection problems for networks with additional information</dc:title>
   <dc:creator>Gutiérrez García-Pardo, Inmaculada</dc:creator>
   <dc:creator>Gómez González, Daniel</dc:creator>
   <dc:creator>Castro Cantalejo, Javier</dc:creator>
   <dc:creator>Espínola Vílchez, María Rosario</dc:creator>
   <dc:contributor>Kahraman, Cengiz</dc:contributor>
   <dc:subject>004.6</dc:subject>
   <dc:subject>51</dc:subject>
   <dc:subject>519.2</dc:subject>
   <dc:subject>Fuzzy clustering</dc:subject>
   <dc:subject>Networks</dc:subject>
   <dc:subject>Community detection</dc:subject>
   <dc:subject>Fuzzy graph</dc:subject>
   <dc:subject>Matemáticas (Matemáticas)</dc:subject>
   <dc:subject>Estadística</dc:subject>
   <dc:subject>1209.03 Análisis de Datos</dc:subject>
   <dc:subject>12 Matemáticas</dc:subject>
   <dc:subject>1209 Estadística</dc:subject>
   <dc:description>In this work we introduce the notion of the weighted graph associated with a fuzzy measure. Having a finite set of elements between which there exists an affinity fuzzy relation, we propose the definition of a group based on that affinity fuzzy relation between the individuals. Then, we propose an algorithm based on the Louvain’s method to deal with community detection problems with additional information independent of the graph. We also provide a particular method to solve community detection problems over extended fuzzy graphs. Finally, we test the performance of our proposal by means of some detailed computational tests calculated in several benchmark models.</dc:description>
   <dc:description>Ministerio de Ciencia e Innovación (España) </dc:description>
   <dc:description>Depto. de Estadística y Ciencia de los Datos</dc:description>
   <dc:description>Fac. de Estudios Estadísticos</dc:description>
   <dc:description>TRUE</dc:description>
   <dc:description>pub</dc:description>
   <dc:date>2024-02-07T13:36:37Z</dc:date>
   <dc:date>2024-02-07T13:36:37Z</dc:date>
   <dc:date>2020</dc:date>
   <dc:type>journal article</dc:type>
   <dc:type>VoR</dc:type>
   <dc:identifier>https://hdl.handle.net/20.500.14352/99999</dc:identifier>
   <dc:identifier>1064-1246</dc:identifier>
   <dc:identifier>10.3233/JIFS-189091</dc:identifier>
   <dc:identifier>1875-8967</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:relation>info:eu-repo/grantAgreement/MINECO//MTM2015-70550-P/ES/ANALISIS JUEGO-TEORICO DE LAS REDES SOCIALES/</dc:relation>
   <dc:relation>info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-096509-B-I00/ES/GESTION INTELIGENTE DE INFORMACION BORROSA/</dc:relation>
   <dc:relation>info:eu-repo/grantAgreement/MINECO//TIN2015-66471-P/ES/TECNICAS DE OBTENCION, PROCESAMIENTO Y REPRESENTACION DE INFORMACION DIFUSA PARA LA TOMA DE DECISIONES/</dc:relation>
   <dc:relation>Gutiérrez, Inmaculada et al. ‘Fuzzy Measures: A Solution to Deal with Community Detection Problems for Networks with Additional Information’. 1 Jan. 2020 : 6217 – 6230</dc:relation>
   <dc:rights>restricted access</dc:rights>
   <dc:format>application/pdf</dc:format>
   <dc:publisher>IOS Press</dc:publisher>
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