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Privacy-preserving hybrid collaborative filtering on cross distributed data
(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 ...
Arbitrarily distributed data-based recommendations with privacy
(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 ...
Privacy-Preserving Svd-Based Collaborative Filtering on Partitioned Data
(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
(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 ...
Efficient Integrity Verification for Outsourced Collaborative Filtering
(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 ...
Privacy-Preserving Collaborative Filtering on Overlapped Ratings
(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 Risks for Multi-Criteria Collaborative Filtering Systems
(IEEE, 2017)
In case that individuals feel their privacy is violated while using any recommender system, they might be willing to declare incorrect information or even completely refuse to use such services. To relieve customer concerns, ...
Privacy-preserving Eigentaste-based collaborative filtering
(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 ...
Maskelenmiş Veriler için Kümeleme-Tabanlı Şilin Atak Tespit Yöntemi
(2016)
İnternet'in yaygınlaşması ile beraber hem ortak filtreleme hem de mahremiyetin korunması artan ilgi görmektedir. Mahremiyeti koruyarak doğru önerileri hızlı bir şekilde kullanıcıya sunmak üzere mahremiyettabanlı ortak ...
Olasılıksal Kaba Kümeler Teorisi Yaklaşımı İle Ekg Verilerinin Sınıflandırılması
(2016)
Sınıflandırma, bilgisayar mühendisliğinde bir veri kümesinin, uzmanlar yerine bilgisayarlar tarafından, özellikleri aracılığı ile gruplanması işlemidir. Kaba kümeler teorisi son yıllarda sınıflandırma problemlerinde gerekli ...