Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/7682
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sert, Onur Can | - |
dc.contributor.author | Dursun, Kayhan | - |
dc.contributor.author | Özyer, Tansel | - |
dc.contributor.author | Jida, Jamal | - |
dc.contributor.author | Alhajj, Reda | - |
dc.date.accessioned | 2021-09-11T15:58:49Z | - |
dc.date.available | 2021-09-11T15:58:49Z | - |
dc.date.issued | 2012 | en_US |
dc.identifier.issn | 0948-695X | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/7682 | - |
dc.description.abstract | Multi objective clustering is one focused area of multi objective optimization. Multi objective optimization attracted many researchers in several areas over a decade. Utilizing multi objective clustering mainly considers multiple objectives simultaneously and results with several natural clustering solutions. Obtained result set suggests different point of views for solving the clustering problem. This paper assumes all potential solutions belong to different experts and in overall; ensemble of solutions finally has been utilized for finding the final natural clustering. We have tested on categorical datasets and compared them against single objective clustering result in terms of purity and distance measure of k-modes clustering. Our clustering results have been assessed to find the most natural clustering. Our results get hold of existing classes decided by human experts. | en_US |
dc.description.sponsorship | Scientific and Technical Research Council of TurkeyTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [Tubitak EEEAG 109E241] | en_US |
dc.description.sponsorship | This paper is part of the project sponsored by Scientific and Technical Research Council of Turkey (Tubitak EEEAG 109E241). We would like to thank for their support. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Graz Univ Technolgoy, Inst Information Systems Computer Media-Iicm | en_US |
dc.relation.ispartof | Journal of Universal Computer Science | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Multi-Objective Clustering | en_US |
dc.subject | NSGA-II | en_US |
dc.subject | h-confidence | en_US |
dc.title | The Unification and Assessment of Multi-Objective Clustering Results of Categorical Datasets With H-Confidence Metric | en_US |
dc.type | Article | en_US |
dc.department | Faculties, Faculty of Engineering, Department of Computer Engineering | en_US |
dc.department | Fakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | tr_TR |
dc.identifier.volume | 18 | en_US |
dc.identifier.issue | 4 | en_US |
dc.identifier.startpage | 507 | en_US |
dc.identifier.endpage | 531 | en_US |
dc.identifier.wos | WOS:000303600100004 | en_US |
dc.identifier.scopus | 2-s2.0-84862601539 | en_US |
dc.institutionauthor | Özyer, Tansel | - |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | Q2 | - |
item.openairetype | Article | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | 02.1. 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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