Konu "Robustness" için Makale Koleksiyonu listeleme
Toplam kayıt 6, listelenen: 1-6
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Designing shilling attacks on disguised binary data
(Inderscience Enterprises LTD, 2017)Privacy-preserving collaborative filtering methods are effectual ways of coping with information overload problem while protecting confidential data. Their success depends on the quality of the collected data. However, ... -
Robustness analysis of arbitrarily distributed data-based recommendation methods
(Pergamon-Elsevier Science LTD, 2016)Due to different shopping routines of people, rating preferences of many customers might be partitioned between two parties. Since two different e-companies might sell products from the same range to the identical set of ... -
Robustness analysis of naïve Bayesian classifier-based collaborative filtering
(Springer Verlag, 2013)In this study, binary forms of previously defined basic shilling attack models are proposed and the robustness of naïve Bayesian classifierbased collaborative filtering algorithm is examined. Real data-based experiments ... -
Robustness analysis of privacy-preserving model-based recommendation schemes
(Pergamon-Elsevier Science LTD, 2014)Privacy-preserving model-based recommendation methods are preferable over privacy-preserving memory-based schemes due to their online efficiency. Model-based prediction algorithms without privacy concerns have been ... -
Shilling Attacks Against Memory-Based Privacy-Preserving Recommendation Algorithms
(Ksii-Kor Soc Internet Information, 2013)Privacy-preserving collaborative filtering schemes are becoming increasingly popular because they handle the information overload problem without jeopardizing privacy. However, they may be susceptible to shilling or profile ... -
Shilling attacks against recommender systems: a comprehensive survey
(Springer, 2014)Online vendors employ collaborative filtering algorithms to provide recommendations to their customers so that they can increase their sales and profits. Although recommendation schemes are successful in e-commerce sites, ...