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dc.contributor.author
Murillo, Javier
dc.contributor.author
Guillaume, Serge
dc.contributor.author
Sari, Tewfik
dc.contributor.author
Bulacio, Pilar Estela
dc.date.available
2022-07-19T17:43:42Z
dc.date.issued
2020-04
dc.identifier.citation
Murillo, Javier; Guillaume, Serge; Sari, Tewfik; Bulacio, Pilar Estela; An algorithm for computing the generalized interaction index for k-maxitive fuzzy measures; IOS Press; Journal Of Intelligent And Fuzzy Systems; 38; 4; 4-2020; 4127-4137
dc.identifier.issn
1064-1246
dc.identifier.uri
http://hdl.handle.net/11336/162551
dc.description.abstract
Fuzzy measures are used for modeling interactions between a set of elements. Simplified fuzzy measures, as k -maxitive measures, were proposed in the literature for complexity and semantic considerations. In order to analyze the importance of a coalition in the fuzzy measure, the use of indices is required. This work focuses on the generalized interaction index, gindex . Its computation requires many resources in both time and space. Following the efforts to reduce the complexity of fuzzy measure identification, this work presents two algorithms to compute the gindex for k -maxitive measures. The structure of k -maxitive measures makes possible to compute the gindex considering the coalitions at level k and, for each of them, the number of coalitions sharing the same coefficient (called inheritors). The first algorithm deals with the space complexity and the second one also optimizes the runtime by not generating, but only counting, the number of inheritors. While counting the number of descendants is easy, this is not the case for the number of inheritors due to all the inheritors of previous considered coalitions have to be taken into account. The two proposed algorithms are tested with synthetic k -maxitive measures showing that the second algorithm is around 4 times faster than the first one.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
IOS Press
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
FUZZY MEASURES
dc.subject
SHAPLEY INDEX
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INTERACTION INDEX
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K-MAXITIVE MEASURES
dc.subject.classification
Otras Ciencias de la Computación e Información
dc.subject.classification
Ciencias de la Computación e Información
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
An algorithm for computing the generalized interaction index for k-maxitive fuzzy measures
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2021-08-27T20:21:10Z
dc.journal.volume
38
dc.journal.number
4
dc.journal.pagination
4127-4137
dc.journal.pais
Países Bajos
dc.journal.ciudad
Amsterdam
dc.description.fil
Fil: Murillo, Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina. Universidad Nacional de Rosario; Argentina
dc.description.fil
Fil: Guillaume, Serge. Université Montpellier II; Francia
dc.description.fil
Fil: Sari, Tewfik. Université Montpellier II; Francia
dc.description.fil
Fil: Bulacio, Pilar Estela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentina. Universidad Nacional de Rosario; Argentina
dc.journal.title
Journal Of Intelligent And Fuzzy Systems
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.medra.org/servlet/aliasResolver?alias=iospress&doi=10.3233/JIFS-190403
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.3233/JIFS-190403
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