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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 ...
Private predictions on hidden Markov models
(Springer, 2010)
Hidden Markov models (HMMs) are widely used in practice to make predictions. They are becoming increasingly popular models as part of prediction systems in finance, marketing, bio-informatics, speech recognition, signal ...
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 ...
Privacy-preserving SOM-based recommendations on horizontally distributed data
(Elsevier Science BV, 2012)
To produce predictions with decent accuracy, collaborative filtering algorithms need sufficient data. Due to the nature of online shopping and increasing amount of online vendors, different customers' preferences about the ...
Estimating Kriging-based predictions with privacy
(2013)
Kriging is a well-known prediction method. It interpolates the value of an unmeasured location from nearby measured locations. In a traditional Kriging interpolation, a client (an entity that is looking for a prediction ...
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 ...
Privacy-Preserving Random Projection-Based Recommendations Based on Distributed Data
(World Scientific Publ Co Pte LTD, 2013)
Providing recommendations based on distributed data has received an increasing amount of attention because it offers several advantages. Online vendors who face problems caused by a limited amount of available data want ...
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 ...