Yazar "Yakut, İbrahim" için listeleme
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Achieving private SVD-based recommendations on inconsistently masked data
Yakut, İbrahim; Polat, H. (Tafford Publishing, 2008)Users' concerns about private data might be different and they want various privacy levels. Therefore, they might decide to mask their data differently to achieve required privacy levels. Providing collaborative filtering ... -
Arbitrarily distributed data-based recommendations with privacy
Yakut, İbrahim; Polat, Hüseyin (Elsevier Science BV, 2012)Collaborative filtering (CF) systems use customers' preferences about various products to offer recommendations. Providing accurate and reliable predictions is vital for both e-commerce companies and their customers. To ... -
Çoklu ölçüt oy değerleri üzerinden veri madenciliği
Türkoğlu, Tuğba (Anadolu Üniversitesi, 2016)Bilgi ve iletişim teknolojilerinin gelişmesi, müşterilerin ürün ve hizmetler hakkında görüş, yorum ve değerlendirmelerini internet üzerinden paylaşma imkânı sunmuştur. Müşterilerin bu ürünleri değerlendirirken birden fazla ... -
Efficient Integrity Verification for Outsourced Collaborative Filtering
Vaidya, Jaideep; Yakut, İbrahim; Basu, Anirban (IEEE, 2014)Collaborative filtering (CF) over large datasets requires significant computing power. Due to this data owning organizations often outsource the computation of CF (including some abstraction of the data itself) to a public ... -
Efficient paillier cryptoprocessor for privacy-preserving data mining
San, İsmail; At, Nuray; Yakut, İbrahim; Polat, Hüseyin (Wiley-Hindawi, 2016)Paillier cryptosystem is extensively utilized as a homomorphic encryption scheme to ensure privacy requirements in many privacy-preserving data mining schemes. However, overall performance of the applications employing ... -
Estimating NBC-based recommendations on arbitrarily partitioned data with privacy
Yakut, İbrahim; Polat, Hüseyin (Elsevier, 2012)Providing partitioned data-based recommendations has been receiving increasing attention due to mutual advantages. In case of limited data, it is not likely to estimate accurate and reliable predictions. Therefore. e-commerce ... -
Pcf: Projection-Based Collaborative Filtering
Yakut, İbrahim; Polat, Hüseyin; Koç, Mehmet (Scitepress, 2010)Collaborative filtering (CF) systems are effective solutions for information overload problem while contributing web personalization. Different memory-based algorithms operating over entire data set have been utilized for ... -
Privacy-preserving collaborative filtering on arbitrarily partitioned data
Yakut, İbrahim (Anadolu Üniversitesi, 2012)Data collected for collaborative filtering purposes might be arbitrarily partitioned between two parties, even rival companies. Online vendors might have insufficient user ratings. Scarce data then might cause offering ... -
Privacy-Preserving Collaborative Filtering on Overlapped Ratings
Memiş, Burak; Yakut, İbrahim (IEEE Computer Soc, 2013)To promote recommendation services through prediction quality, there are some privacy-preserving collaborative filtering (PPCF) solutions enabling e-commerce parties to collaborate on partitioned data. It is almost probable ... -
Privacy-preserving dimensionality reduction-based collaborative filtering
Yakut, İbrahim (Anadolu Üniversitesi, 2008)İşbirlikçi filtreleme (İF) sistemleri birçok elektronik ticaret sitesi tarafından kullanılmaktadır. Fakat bu sistemler gizlilik ölçütlerini sağlamada yetersiz kalmaktadırlar. Birçok internet kullanıcısı gizlilik endişelerinden ... -
Privacy-preserving Eigentaste-based collaborative filtering
Yakut, İbrahim; Polat, Hüseyin (Springer-Verlag Berlin, 2007)With the evolution of e-commerce, privacy is becoming a major concern. Many e-companies employ collaborative filtering (CF) techniques to increase their sales by providing truthful recommendations to customers. Many ... -
Privacy-preserving hybrid collaborative filtering on cross distributed data
Yakut, İbrahim; Polat, Hüseyin (Springer London LTD, 2012)Data collected for collaborative filtering (CF) purposes might be cross distributed between two online vendors, even competing companies. Such corporations might want to integrate their data to provide more precise and ... -
Privacy-preserving item-based recommendations over partitioned data with overlaps
Yakut, İbrahim; Vaidya, J. (Inderscience Enterprises Ltd., 2017)User ratings are vital elements to drive recommender systems and, in the case of an insufficient amount of ratings, companies may prefer to operate recommender services over partitioned data. To make this feasible, there ... -
Privacy-Preserving Svd-Based Collaborative Filtering on Partitioned Data
Yakut, İbrahim; Polat, Hüseyin (World Scientific Publ Co Pte LTD, 2010)Collaborative filtering (CF) systems are widely employed by many e-commerce sites for providing recommendations to their customers. To recruit new customers, retain the current ones, and gain competitive edge over competing ... -
Privacy-Preserving Two-Party Collaborative Filtering on Overlapped Ratings
Memiş, Burak; Yakut, İbrahim (Ksii-Kor Soc Internet Information, 2014)To promote recommendation services through prediction quality, some privacy-preserving collaborative filtering solutions are proposed to make e-commerce parties collaborate on partitioned data. It is almost probable that ... -
Privacy-preserving two-party collaborative filtering on overlapped ratings
Memiş, Burak (Anadolu Üniversitesi, 2016)Tavsiye hizmetlerini öneri kalitesini artırarak geliştirmek için önerilen gizlilik koruyucu ortak filtreleme çözümleri e-ticaret şirketlerinin paylaşılmış veri üzerinden işbirliği yapmalarına imkân sağlar. İki tarafın aynı ... -
A Survey of Privacy-Preserving Collaborative Filtering Schemes
Bilge, Alper; Kaleli, Cihan; Yakut, İbrahim; Güneş, İhsan; Polat, Hüseyin (World Scientific Publ Co Pte LTD, 2013)With increasing need for preserving confidential data while providing recommendations, privacy-preserving collaborative filtering has been receiving increasing attention. To make data owners feel more comfortable while ...
