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dc.contributor.convenorMike Ewing and Felix Mavondoen_AU
dc.contributor.authorE. Voges, Kevinen_US
dc.contributor.authorPope, Nigelen_US
dc.contributor.editorDr Dewi Tojiben_US
dc.date.accessioned2017-05-03T12:47:05Z
dc.date.available2017-05-03T12:47:05Z
dc.date.issued2009en_US
dc.date.modified2010-06-10T22:20:58Z
dc.identifier.refurihttp://anzmac2009.org/en_AU
dc.identifier.urihttp://hdl.handle.net/10072/29772
dc.description.abstractCluster analysis is a fundamental data analysis technique, but many clustering methods have limitations, such as requiring initial starting points and requiring that the number of clusters be specified in advance. This paper describes an evolutionary algorithm based rough clustering algorithm, which is able to overcome these limitations. Rough clusters use sub-clusters called lower and upper approximations. The lower approximation of a rough cluster contains objects that only belong to that cluster, while the upper approximation contains objects that can belong to more than one cluster. The approach therefore allows for multiple cluster membership for data objects. This rough clustering algorithm was tested on a large data set of perceptions of city destination image attributes, and some preliminary results are presented.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent22584 bytes
dc.format.extent135780 bytes
dc.format.mimetypetext/plain
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherPromaco Conventions (for ANZMAC)en_US
dc.publisher.placeCanning Bridge, Western Australiaen_US
dc.publisher.urihttp://anzmac2009.org/en_AU
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofconferencenameAustralian and New Zealand Marketing Academy (ANZMAC) Conference 2009en_US
dc.relation.ispartofconferencetitleANZMAC 2009en_US
dc.relation.ispartofdatefrom2009-11-30en_US
dc.relation.ispartofdateto2009-12-02en_US
dc.relation.ispartoflocationMelbourne, Australiaen_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchMarketing Research Methodologyen_US
dc.subject.fieldofresearchcode150505en_US
dc.titleAnalysing Destination Image Data Using Rough Clusteringen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.rights.copyrightCopyright 2009 ANZMAC. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the conference website for access to the definitive, published version.en_AU
gro.date.issued2009
gro.hasfulltextFull Text


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    Contains papers delivered by Griffith authors at national and international conferences.

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