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dc.contributor.authorBilge, Alper
dc.contributor.authorPolat, Hüseyin
dc.date.accessioned2019-10-21T19:44:18Z
dc.date.available2019-10-21T19:44:18Z
dc.date.issued2012
dc.identifier.issn0957-4174
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2011.09.094
dc.identifier.urihttps://hdl.handle.net/11421/19851
dc.descriptionWOS: 000297823300168en_US
dc.description.abstractCollaborative filtering (CF) is one of the most efficient techniques to produce personalized recommendations and to deal with the information overload of modern times. Although CF techniques have immensely useful filtering capabilities, many CF systems have challenging problems like scalability, accuracy, and privacy. One approach to enhance scalability of such systems is to apply discrete wavelet transformation (DWT) techniques. DWT-based CF schemes significantly overcome the scalability problem. However, they fail to protect individual users' privacy. Moreover, although such schemes provide accurate predictions, the quality of the recommendations provided by DWT-based CF schemes can be further improved by applying some preprocessing methods. In this study, we propose privacy-preserving schemes to produce accurate predictions based on DWT efficiently without deeply exposing customers' privacy. We also recommend methods to order items before applying DWT to boost accuracy. After evaluating our schemes in terms of privacy and supplementary costs, we perform real data-based experiments to scrutinize the proposed schemes in terms of accuracy. Experimental results show that our privacy-preserving methods are able to offer recommendations with decent accuracy. Moreover, our outcomes show that our methods utilized to sort items improve accuracy. We finally provide some suggestions and explain future worksen_US
dc.description.sponsorshipTUBITAK [108E221]en_US
dc.description.sponsorshipThis work is supported by Grant 108E221 from TUBITAK.en_US
dc.language.isoengen_US
dc.publisherPergamon-Elsevier Science LTDen_US
dc.relation.isversionof10.1016/j.eswa.2011.09.094en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPrivacyen_US
dc.subjectDwten_US
dc.subjectCollaborative Filteringen_US
dc.subjectAccuracyen_US
dc.subjectPerformanceen_US
dc.subjectPreprocessingen_US
dc.titleAn improved privacy-preserving DWT-based collaborative filtering schemeen_US
dc.typearticleen_US
dc.relation.journalExpert Systems With Applicationsen_US
dc.contributor.departmentAnadolu Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.identifier.volume39en_US
dc.identifier.issue3en_US
dc.identifier.startpage3841en_US
dc.identifier.endpage3854en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US]
dc.contributor.institutionauthorBilge, Alper


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