Chapter List

Overview

We discuss some methods for constructing recommender systems. An important feature of the methods studied here is that we assume the availability of a description, representation, of the objects being considered for recommendation. The approaches studied here differ from collaborative filtering in that we only use preferences information from the individual for whom we are providing the recommendation and make no use the preferences of other collaborators. We provide a detailed discussion of the construction of the representation schema used. We consider two sources of information about the users preferences. The first are direct statements about the type of objects the user likes. The second source of information comes from ratings of objects which the user has experienced.

1.1 Introduction

Recommender systems [Resnick and Varian (1997)] are an important part of many websites and play a central role in the Ecommerce effort toward personalization and customization. The current generation of recommender systems predominantly use collaborative filtering...