Konu "Collaborative Filtering" için Makale Koleksiyonu listeleme
Toplam kayıt 20, listelenen: 1-20
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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 ... -
A comparison of clustering-based privacy-preserving collaborative filtering schemes
(Elsevier, 2013)Privacy-preserving collaborative filtering (PPCF) methods designate extremely beneficial filtering skills without deeply jeopardizing privacy. However, they mostly suffer from scalability, sparsity, and accuracy problems. ... -
Deriving private data in partitioned data-based privacy-preserving collaborative filtering systems
(Gazi University, Fac Engineering Architecture, 2017)Collaborative filtering algorithms need enough data to provide accurate and reliable predictions. Hence, two e-commerce sites holding insufficient data may want to provide predictions on their partitioned data with privacy. ... -
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, ... -
Detecting shilling attacks in private environments
(Springer, 2016)Privacy-preserving collaborative filtering algorithms are successful approaches. However, they are susceptible to shilling attacks. Recent research has increasingly focused on collaborative filtering to protect against ... -
Effects of similarity measures on the quality of predictions
(2013)Providing accurate predictions efficiently is vital for the success of recommender systems. There are various factors that might affect the quality of the predictions and online performance. Similarity metric used to ... -
An entropy-based neighbor selection approach for collaborative filtering
(Elsevier, 2014)Collaborative filtering is an emerging technology to deal with information overload problem guiding customers by offering recommendations on products of possible interest. Forming neighborhood of a user/item is the crucial ... -
An improved privacy-preserving DWT-based collaborative filtering scheme
(Pergamon-Elsevier Science LTD, 2012)Collaborative 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 ... -
A new hybrid recommendation algorithm with privacy
(Wiley-Blackwell, 2012)Providing accurate and dependable recommendations efficiently while preserving privacy is essential for e-commerce sites to recruit new customers and keep the existing ones. Such sites might be able to increase their sales ... -
P2P collaborative filtering with privacy
(Tubitak Scientific & Technical Research Council Turkey, 2010)With the evolution of the Internet and e-commerce, collaborative filtering (CF) and privacy-preserving collaborative filtering (PPCF) have become popular The goal in CF is to generate predictions with decent accuracy, ... -
Privacy-preserving item-based recommendations over partitioned data with overlaps
(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 normalized ratings-based weighted slope one predictor
(WITPress, 2016)Weighted Slope One predictor is proposed as a model-based collaborative filtering algorithm based on user ratings. The predictor is able to efficiently provide accurate predictions. The scheme utilizes user's true ratings. ... -
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 ... -
Reconstructing rated items from perturbed data
(Elsevier Science BV, 2016)The basic idea behind privacy-preserving collaborative filtering schemes is to prevent data collectors from deriving the actual rating values and the rated items. Different data perturbation methods have been proposed to ... -
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 multi-criteria collaborative filtering algorithms against shilling attacks
(Pergamon-Elsevier Science LTD, 2019)Collaborative filtering is an emerging recommender system technique that aims guiding users based on other customers preferences with behavioral similarities. Such correspondences are located based on preference history ... -
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, ... -
A Survey of Privacy-Preserving Collaborative Filtering Schemes
(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 ...