Ara
Toplam kayıt 5, listelenen: 1-5
A Multi-Criteria Item-based Collaborative Filtering Framework
(IEEE, 2014)
Collaborative filtering methods are utilized to provide personalized recommendations for users in order to alleviate information overload problem in different domains. Traditional collaborative filtering methods operate ...
Achieving Optimal Privacy in Trust-Aware Social Recommender Systems
(Springer-Verlag Berlin, 2010)
Collaborative filtering (CF) recommenders are subject to numerous shortcomings such as centralized processing, vulnerability to shilling attacks, and most important of all privacy. To overcome these obstacles, researchers ...
A multi-criteria item-based collaborative filtering framework
(IEEE Computer Society, 2014)
Collaborative filtering methods are utilized to provide personalized recommendations for users in order to alleviate information overload problem in different domains. Traditional collaborative filtering methods operate ...
On Binary Similarity Measures for Privacy-Preserving Top-N Recommendations
(Scitepress, 2010)
Collaborative filtering (CF) algorithms fundamentally depend on similarities between users and/or items to predict individual preferences. There are various binary similarity measures like Kulzinslcy, Sokal-Michener, Yule, ...
Similar or Dissimilar Users? Or Both?
(IEEE Computer Soc, 2009)
E-commerce sites utilize collaborative filtering (CF) techniques to offer recommendations to their customers. To recruit new customers and keep the current ones, it is imperative for online vendors to provide accurate ...