Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6389
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dc.contributor.authorOzyer, Tansel-
dc.contributor.authorAlhajj, Reda-
dc.contributor.authorBarker, Ken-
dc.date.accessioned2021-09-11T15:36:12Z-
dc.date.available2021-09-11T15:36:12Z-
dc.date.issued2006en_US
dc.identifier.citation7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2006) -- SEP 20-23, 2006 -- Univ Burgos, Burgos, SPAINen_US
dc.identifier.isbn3-540-45485-3-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6389-
dc.description.abstractThis paper presents a clustering approach that integrates multi-objective optimization, weighted k-means and validity analysis in an iterative process to automatically estimate the number of clusters, and then partition the whole given data to produce the most natural clustering. The proposed approach has been tested on real-life dataset; results of both weighted and unweighed k-means are reported to demonstrate applicability and effectiveness of the proposed approach.en_US
dc.language.isoenen_US
dc.publisherSpringer-Verlag Berlinen_US
dc.relation.ispartofIntelligent Data Engineering And Automated Learning - Ideal 2006, Proceedingsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subject[No Keywords]en_US
dc.titleClustering by Integrating Multi-Objective Optimization With Weighted K-Means and Validity Analysisen_US
dc.typeConference Objecten_US
dc.relation.ispartofseriesLECTURE NOTES IN COMPUTER SCIENCEen_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.identifier.volume4224en_US
dc.identifier.startpage454en_US
dc.identifier.endpage463en_US
dc.identifier.wosWOS:000241790900055en_US
dc.identifier.scopus2-s2.0-33750563824en_US
dc.institutionauthorÖzyer, Tansel-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conference7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2006)en_US
dc.identifier.scopusqualityQ2-
item.openairetypeConference Object-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.1. Department of Artificial Intelligence Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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