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Toplam kayıt 21, listelenen: 1-10
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 ...
Privacy-Preserving Kriging Interpolation on Distributed Data
(Springer-Verlag Berlin, 2014)
Kriging is one of the most preferred geostatistical methods in many engineering fields. Basically, it creates a model using statistical properties of all measured points in the region, where a prediction value is sought. ...
Effects of Inconsistently Masked Data Using RPT on CF with Privacy
(Assoc Computing Machinery, 2007)
Randomized perturbation techniques (RPT) are applied to perturb the customers' private data to protect privacy while providing accurate referrals. In the RPT-based collaborative filtering (CF) with privacy schemes, proposed ...
Finding the State Sequence Maximizing P(O, I vertical bar lambda) on Distributed HMMs with Privacy
(IEEE, 2009)
Hidden Markov models (HMMs) are widely used by many applications for forecasting purposes. They are increasingly becoming popular models as part of prediction systems in finance, marketing, bio-informatics, speech recognition, ...
Robustness Analysis of Naive Bayesian Classifier-Based Collaborative Filtering
(Springer-Verlag Berlin, 2013)
In this study, binary forms of previously defined basic shilling attack models are proposed and the robustness of naive Bayesian classifier-based collaborative filtering algorithm is examined. Real data-based experiments ...
Providing Private Recommendations on Personal Social Networks
(Springer-Verlag Berlin, 2010)
Personal social networks are recently used to offer recommendations. Due to privacy concerns, privacy protection while generating accurate referrals is imperative. Since accuracy and privacy are conflicting goals, providing ...
Providing private recommendations using naive Bayesian classifier
(Springer-Verlag Berlin, 2007)
Today's CF systems fail to protect users' privacy. Without privacy protection, it becomes a challenge to collect sufficient and high quality data for CF. With privacy protection, users feel comfortable to provide more ...
Privacy-preserving kriging interpolation on distributed data
(Springer Verlag, 2014)
Kriging is one of the most preferred geostatistical methods in many engineering fields. Basically, it creates a model using statistical properties of all measured points in the region, where a prediction value is sought. ...
Pcf: Projection-Based Collaborative Filtering
(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 ...
Providing naive Bayesian classifier-based private recommendations on partitioned data
(Springer-Verlag Berlin, 2007)
Data collected for collaborative filtering (CF) purposes might be split between various parties. Integrating such data is helpful for both e-companies and customers due to mutual advantageous. However, due to privacy ...