Collaborative filtering (CF) is one of the most successful approaches for recommendation. In this paper, we propose two hybrid CF algorithms, sequential mixture CF and joint mixtu...
Xiaoyuan Su, Russell Greiner, Taghi M. Khoshgoftaa...
In this paper we present a simple to implement truly online large margin version of the Perceptron ranking (PRank) algorithm, called the OAP-BPM (Online Aggregate Prank-Bayes Poin...
Collaborative filtering uses a database about consumers’ preferences to make personal product recommendations and is achieving widespread success in both E-Commerce and Informat...
Kai Yu, Xiaowei Xu, Martin Ester, Hans-Peter Krieg...
We show that the standard memory-based collaborative filtering rating prediction algorithm using the Pearson correlation can be improved by adapting user ratings using linear reg...
Abstract. With the amount of available information on the Web growing rapidly with each day, the need to automatically filter the information in order to ensure greater user effici...
Miha Grcar, Dunja Mladenic, Blaz Fortuna, Marko Gr...