An algorithmic framework for performing collaborative filtering

Abstract

Automated collaborative filtering is quickly becoming a popular technique for reducing information overload, often as a technique to complement content-based information filtering systems. In this paper we present an algorithmic framework for performing collaborative filtering and new algorithmic elements that increase the accuracy of collaborative prediction algorithms. We then present a set of recommendations on selection of the right collaborative filtering algorithmic components.