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dc.contributor.authorSevilla-Villanueva, Beatriz
dc.contributor.authorGibert, Karina
dc.contributor.authorSànchez-Marrè, Miquel
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2016-11-09T12:25:13Z
dc.date.issued2016-10
dc.identifier.citationSevilla-Villanueva, Beatriz, Gibert, Karina, Sànchez-Marrè, Miquel. A methodology for maintaining consistency between conceptual interpretations of nested partitions. A: "Artificial Intelligence Research and Development: Proceedings of the 19th International Conference of the Catalan Association for Artificial Intelligence, Barcelona, Catalonia, Spain, October 19-21, 2016". Amsterdam: IOSPress, 2016, p. 147-156.
dc.identifier.isbn978-1-61499-695-8
dc.identifier.urihttp://hdl.handle.net/2117/95947
dc.description.abstractThe relationship between interpretations of nested partitions is analyzed in this work, since there are multiple situations where a refinement of the original partition arises. As a result, a new methodology NCI-IMS is proposed in order to maintain the consistency between interpretations of nested partitions. This methodology extends a previous methodology that obtains classes’ descriptors by determining the significance’s robustness of the characteristics significance. Then, NCI-IMS takes advantage of the descriptors robustness obtaining a deeper analysis of the relations between superclass’s and subclasses’ descriptors.
dc.format.extent10 p.
dc.language.isoeng
dc.publisherIOSPress
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Economia i organització d'empreses
dc.subject.lcshData mining -- Analysis
dc.subject.lcshTechnological innovations
dc.subject.otherClustering
dc.subject.otherCluster Interpretation
dc.subject.otherNested Partitions
dc.titleA methodology for maintaining consistency between conceptual interpretations of nested partitions
dc.typePart of book or chapter of book
dc.subject.lemacMineria de dades
dc.subject.lemacProgramari -- Desenvolupament
dc.subject.lemacInnovacions tecnològiques
dc.contributor.groupUniversitat Politècnica de Catalunya. KEMLG - Grup d'Enginyeria del Coneixement i Aprenentatge Automàtic
dc.identifier.doi10.3233/978-1-61499-696-5-147
dc.relation.publisherversionhttp://www.iospress.nl/book/artificial-intelligence-research-and-development-13/
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac19193416
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
local.citation.authorSevilla-Villanueva, Beatriz; Gibert, Karina; Sànchez-Marrè, Miquel
local.citation.pubplaceAmsterdam
local.citation.publicationNameArtificial Intelligence Research and Development: Proceedings of the 19th International Conference of the Catalan Association for Artificial Intelligence, Barcelona, Catalonia, Spain, October 19-21, 2016
local.citation.startingPage147
local.citation.endingPage156


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