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Optimization clustering techniques on register unemployment data

dc.contributor.authorBalsa, Carlos
dc.contributor.authorNunes, Alcina
dc.contributor.authorBarros, Elisa
dc.date.accessioned2018-03-23T10:02:35Z
dc.date.available2018-03-23T10:02:35Z
dc.date.issued2015
dc.description.abstractAn important strategy for data classification consists in organising data points in clusters. The k-means is a traditional optimisation method applied to cluster data points. Using a labour market database, aiming the segmentation of this market taking into account the heterogeneity resulting from different unemployment characteristics observed along the Portuguese geographical space, we suggest the application of an alternative method based on the computation of the dominant eigenvalue of a matrix related with the distance among data points. This approach presents results consistent with the results obtained by the k-means.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBalsa, Carlos; Nunes, Alcina; Barros, Elisa (2015). Optimization clustering techniques on register unemployment data. In Almeida, João Paulo; Oliveira, José F.; Pinto, Alberto A. (Eds.) Operational Research e 16th National Conference of the APDIO. p. 19-35. ISBN 978-3-319-20327-0pt_PT
dc.identifier.doi10.1007/978-3-319-20328-7_2pt_PT
dc.identifier.isbn978-3-319-20327-0
dc.identifier.urihttp://hdl.handle.net/10198/16485
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer International Publishingpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectPortuguesept_PT
dc.titleOptimization clustering techniques on register unemployment datapt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferencePlaceBragança, Portugalpt_PT
oaire.citation.endPage35pt_PT
oaire.citation.startPage19pt_PT
oaire.citation.titleOperational Research - IO 2013 - XVI Congress of APDIOpt_PT
oaire.citation.volume4pt_PT
person.familyNameBalsa
person.familyNameNunes
person.familyNameBarros
person.givenNameCarlos
person.givenNameAlcina
person.givenNameElisa
person.identifier1721518
person.identifier.ciencia-idDE1E-2F7A-AAB1
person.identifier.ciencia-id1111-680F-0CAF
person.identifier.orcid0000-0003-2431-8665
person.identifier.orcid0000-0003-4056-9747
person.identifier.orcid0000-0001-8515-695X
person.identifier.ridM-8735-2013
person.identifier.ridM-8259-2013
person.identifier.scopus-author-id23391719100
person.identifier.scopus-author-id55907654000
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationd0e5ccff-9696-4f4f-9567-8d698a6bf17d
relation.isAuthorOfPublicationf96c3560-c1d3-432c-aa84-49982ea86106
relation.isAuthorOfPublication29601d32-5c12-4b5f-84ec-55d83617d04e
relation.isAuthorOfPublication.latestForDiscoveryf96c3560-c1d3-432c-aa84-49982ea86106

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