Rough set based categorical association rule mining in web database

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dc.contributor.authorÜlker E.
dc.contributor.authorSiramkaya E.
dc.contributor.authorArslan A.
dc.date.accessioned2020-03-26T17:19:26Z
dc.date.available2020-03-26T17:19:26Z
dc.date.issued2007
dc.departmentSelçuk Üniversitesien_US
dc.descriptionIAENG Society of Artificial Intelligence;IAENG Society of Bioinformatics;IAENG Society of Computer Science;IAENG Society of Data Mining;IAENG Society of Electrical Engineeringen_US
dc.descriptionInternational MultiConference of Engineers and Computer Scientists 2007, IMECS 2007 -- 21 March 2007 through 23 March 2007 -- Kowloon -- 100960en_US
dc.description.abstractOne of the most studied fields in data mining is association rules field and studied on this field more than database communications recently. In existed methods of association rules discovery, studying of objects as an only one category provides deficiency of algorithms which provide finding of categorical associations. Online text documents on internet provide adequate information sources. In this paper, meaningful and important information from text documents on internet have been tried to discover. Firstly, a preprocessing is applied to these data to reduce data with noisy and after that only adequate data are saved to database to use. In the study, relations are discovered based on person-place-event-date categories. In this paper, it is investigated to how the categorical association rules can be discovered using rough sets and presented as an application.en_US
dc.identifier.endpage1036en_US
dc.identifier.isbn9.78989E+12
dc.identifier.issn2078-0958en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage1032en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/21872
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.relation.ispartofLecture Notes in Engineering and Computer Scienceen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectAssociationsen_US
dc.subjectCategorical association ruleen_US
dc.subjectData miningen_US
dc.subjectRough set theoryen_US
dc.subjectWeb databaseen_US
dc.titleRough set based categorical association rule mining in web databaseen_US
dc.typeConference Objecten_US

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