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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 ...
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 ...
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 ...
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 ...
Providing predictions on distributed HMMs with privacy
(Springer, 2007)
As forecasting is increasingly becoming important, hidden Markov models (HMMs) are widely used for prediction in many applications such as finance, marketing, bioinformatics, speech recognition, and so on. After creating ...
Privacy-preserving kriging interpolation on partitioned data
(Elsevier Science BV, 2014)
Kriging is well-known, frequently applied method in geo-statistics. Its success primarily depends on the total number of measurements for some sample points. If there are sufficient sample points with measurements, kriging ...
SOM-based recommendations with privacy on multi-party vertically distributed data
(Palgrave Macmillan LTD, 2012)
Data collected for providing recommendations can be partitioned among different parties. Offering distributed data-based predictions is popular due to mutual advantages. It is almost impossible to present trustworthy ...
Privacy-Preserving Inverse Distance Weighted Interpolation
(Springer Heidelberg, 2014)
Inverse distance weighted (IDW) interpolation is one of the well-known geo-statistics techniques. On the one hand, one party (server) holding some measurements for specific locations wants to provide predictions; on the ...
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 ...
Modeling and prediction with a class of time delay dynamic neural networks
(Elsevier Science BV, 2007)
In this paper, we propose a time delay dynamic neural network (TDDNN) to track and predict a chaotic time series systems. The application of artificial neural networks to dynamical systems has been constrained by the ...