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Unemployment similarities among portuguese regions - a cluster analysis approach

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Resumo:The regional distribution of the unemployed individual characteristics is of core importance for the development of public policies that can fight the unemployment phenomenon, especially in times of crises. The data mining cluster methodology allows finding groups of regional areas that share the same characteristics for the register unemployed and, therefore, helps in a better understanding of the problem and possible solutions. Preliminary results for the Portuguese regions show a clear division of the territory among four regions – north and south and urban and rural areas of the country – concerning individual characteristics such the gender, age, education or unemployment duration. These results have policy consequences.
Autores principais:Barros, Elisa
Outros Autores:Nunes, Alcina
Assunto:Cluster analysis Data mining Unemployment Portuguese regions
Ano:2010
País:Portugal
Tipo de documento:documento de conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
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author Barros, Elisa
author2 Nunes, Alcina
author2_role author
author_facet Barros, Elisa
Nunes, Alcina
author_role author
contributor_name_str_mv Biblioteca Digital do IPB
country_str PT
creators_json_txt [{\"Person.name\":\"Barros, Elisa\",\"Person.identifier.orcid\":\"0000-0001-8515-695X\"},{\"Person.name\":\"Nunes, Alcina\",\"Person.identifier.orcid\":\"0000-0003-4056-9747\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Biblioteca Digital do IPB
datacite.creators.creator.creatorName.fl_str_mv Barros, Elisa
Nunes, Alcina
datacite.date.Accepted.fl_str_mv 2010-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2011-05-02T14:30:54Z
datacite.date.embargoed.fl_str_mv 2011-05-02T14:30:54Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Cluster analysis
Data mining
Unemployment
Portuguese regions
datacite.titles.title.fl_str_mv Unemployment similarities among portuguese regions - a cluster analysis approach
dc.contributor.none.fl_str_mv Biblioteca Digital do IPB
dc.creator.none.fl_str_mv Barros, Elisa
Nunes, Alcina
dc.date.Accepted.fl_str_mv 2010-01-01T00:00:00Z
dc.date.available.fl_str_mv 2011-05-02T14:30:54Z
dc.date.embargoed.fl_str_mv 2011-05-02T14:30:54Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10198/4134
dc.language.none.fl_str_mv eng
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Cluster analysis
Data mining
Unemployment
Portuguese regions
dc.title.fl_str_mv Unemployment similarities among portuguese regions - a cluster analysis approach
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_c94f
description The regional distribution of the unemployed individual characteristics is of core importance for the development of public policies that can fight the unemployment phenomenon, especially in times of crises. The data mining cluster methodology allows finding groups of regional areas that share the same characteristics for the register unemployed and, therefore, helps in a better understanding of the problem and possible solutions. Preliminary results for the Portuguese regions show a clear division of the territory among four regions – north and south and urban and rural areas of the country – concerning individual characteristics such the gender, age, education or unemployment duration. These results have policy consequences.
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eu_rights_str_mv openAccess
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network_name_str Biblioteca Digital do IPB
oai_identifier_str oai:bibliotecadigital.ipb.pt:10198/4134
organization_str_mv urn:organizationAcronym:ipb
person_str_mv Barros, Elisa
Barros, Elisa
http://orcid.org/0000-0001-8515-695X
0000-0001-8515-695X
Nunes, Alcina
Nunes, Alcina
https://www.ciencia-id.pt/1111-680F-0CAF
1111-680F-0CAF
http://orcid.org/0000-0003-4056-9747
0000-0003-4056-9747
publishDate 2010
reponame_str Biblioteca Digital do IPB
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spelling engporThe regional distribution of the unemployed individual characteristics is of core importance for the development of public policies that can fight the unemployment phenomenon, especially in times of crises. The data mining cluster methodology allows finding groups of regional areas that share the same characteristics for the register unemployed and, therefore, helps in a better understanding of the problem and possible solutions. Preliminary results for the Portuguese regions show a clear division of the territory among four regions – north and south and urban and rural areas of the country – concerning individual characteristics such the gender, age, education or unemployment duration. These results have policy consequences.application/pdfporUnemployment similarities among portuguese regions - a cluster analysis approachPersonalBarros, ElisaDSpacehttp://dspace.org/items/29601d32-5c12-4b5f-84ec-55d83617d04eDSpacehttp://dspace.org/items/29601d32-5c12-4b5f-84ec-55d83617d04eBarrosElisaORCIDhttp://orcid.org0000-0001-8515-695XPersonalNunes, AlcinaDSpacehttp://dspace.org/items/f96c3560-c1d3-432c-aa84-49982ea86106DSpacehttp://dspace.org/items/f96c3560-c1d3-432c-aa84-49982ea86106NunesAlcinaCiência IDhttps://www.ciencia-id.pt1111-680F-0CAFORCIDhttp://orcid.org0000-0003-4056-9747Researcher IDhttps://www.researcherid.comM-8259-2013Scopus Author IDhttps://www.scopus.com55907654000HostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.pt2011-05-02T14:30:54Z20102010-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/4134http://purl.org/coar/access_right/c_abf2open accessCluster analysisData miningUnemploymentPortuguese regions95943 bytesother research producthttp://purl.org/coar/resource_type/c_c94fconference objecthttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/d3eba62f-f2d3-453b-8a45-b46f116c0d5c/downloadBook of Abstracts of the 24th European Conference on Operational Research (EUROXXIV)294Lisboa, Portugal
spellingShingle Unemployment similarities among portuguese regions - a cluster analysis approach
Barros, Elisa
Cluster analysis
Data mining
Unemployment
Portuguese regions
status SINGLETON
subject.fl_str_mv Cluster analysis
Data mining
Unemployment
Portuguese regions
title Unemployment similarities among portuguese regions - a cluster analysis approach
title_full Unemployment similarities among portuguese regions - a cluster analysis approach
title_fullStr Unemployment similarities among portuguese regions - a cluster analysis approach
title_full_unstemmed Unemployment similarities among portuguese regions - a cluster analysis approach
title_short Unemployment similarities among portuguese regions - a cluster analysis approach
title_sort Unemployment similarities among portuguese regions - a cluster analysis approach
topic Cluster analysis
Data mining
Unemployment
Portuguese regions
topic_facet Cluster analysis
Data mining
Unemployment
Portuguese regions
url http://hdl.handle.net/10198/4134
visible 1