Hierarchical cluster analysis of groups of individuals : application to business data

Detalhes bibliográficos
Autor(a) principal: Sousa, Áurea
Data de Publicação: 2014
Outros Autores: Bacelar-Nicolau, Helena, Silva, Osvaldo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.3/3425
Resumo: 3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.
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spelling Hierarchical cluster analysis of groups of individuals : application to business dataHierarchical Cluster AnalysisAffinity CoefficientIndependent Groups of IndividualsVL MethodologyClassical DataSymbolic Data3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.We present one example, in which the data are issued from a questionnaire in order to find satisfaction typologies (with the services provided by an automobile company) of independent groups of individuals. The Agglomerative Hierarchical Cluster Analysis (AHCA) was based on two approaches: one based on a particular case of the generalized weighted affinity coefficient, which deals with classical data, and the other one on the weighted generalized affinity coefficient for the case of symbolic/complex data. Both measures of comparison between elements were combined with classical and probabilistic aggregation criteria. We used the global statistics of levels (STAT) to evaluate the quality of the obtained partitions.ISAST - International Society for the Advancement of Science and TechnologyRepositório da Universidade dos AçoresSousa, ÁureaBacelar-Nicolau, HelenaSilva, Osvaldo2015-04-28T10:05:15Z20142014-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/pdfhttp://hdl.handle.net/10400.3/3425engSousa, Áurea; Bacelar-Nicolau, Helena; Silva, Osvaldo (2014). "Hierarchical Cluster Analysis of Groups of Individuals: Application to Business Data ". Proceedings of the 3rd Stochastic Modeling Techniques and Data Analysis International Conference (SMTDA2014), C. H. Skiadas (Eds.), 2014 ISAST, 719-727.978-618-81257-5-9 (Book)info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-12-20T14:31:27Zoai:repositorio.uac.pt:10400.3/3425Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:25:59.673341Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Hierarchical cluster analysis of groups of individuals : application to business data
title Hierarchical cluster analysis of groups of individuals : application to business data
spellingShingle Hierarchical cluster analysis of groups of individuals : application to business data
Sousa, Áurea
Hierarchical Cluster Analysis
Affinity Coefficient
Independent Groups of Individuals
VL Methodology
Classical Data
Symbolic Data
title_short Hierarchical cluster analysis of groups of individuals : application to business data
title_full Hierarchical cluster analysis of groups of individuals : application to business data
title_fullStr Hierarchical cluster analysis of groups of individuals : application to business data
title_full_unstemmed Hierarchical cluster analysis of groups of individuals : application to business data
title_sort Hierarchical cluster analysis of groups of individuals : application to business data
author Sousa, Áurea
author_facet Sousa, Áurea
Bacelar-Nicolau, Helena
Silva, Osvaldo
author_role author
author2 Bacelar-Nicolau, Helena
Silva, Osvaldo
author2_role author
author
dc.contributor.none.fl_str_mv Repositório da Universidade dos Açores
dc.contributor.author.fl_str_mv Sousa, Áurea
Bacelar-Nicolau, Helena
Silva, Osvaldo
dc.subject.por.fl_str_mv Hierarchical Cluster Analysis
Affinity Coefficient
Independent Groups of Individuals
VL Methodology
Classical Data
Symbolic Data
topic Hierarchical Cluster Analysis
Affinity Coefficient
Independent Groups of Individuals
VL Methodology
Classical Data
Symbolic Data
description 3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.
publishDate 2014
dc.date.none.fl_str_mv 2014
2014-01-01T00:00:00Z
2015-04-28T10:05:15Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.3/3425
url http://hdl.handle.net/10400.3/3425
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Sousa, Áurea; Bacelar-Nicolau, Helena; Silva, Osvaldo (2014). "Hierarchical Cluster Analysis of Groups of Individuals: Application to Business Data ". Proceedings of the 3rd Stochastic Modeling Techniques and Data Analysis International Conference (SMTDA2014), C. H. Skiadas (Eds.), 2014 ISAST, 719-727.
978-618-81257-5-9 (Book)
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv ISAST - International Society for the Advancement of Science and Technology
publisher.none.fl_str_mv ISAST - International Society for the Advancement of Science and Technology
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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