Identifying and Analyzing User Model Information from Collaborative Filtering Datasets

This paper considers the information that can be captured about users from a collaborative filtering dataset. The aims of the paper are to create a user model and to use this model to explain the performance of a collaborative filtering approach. A number of user features are defined and the performance of a collaborative filtering system in producing recommendations for users with different feature values is tested. Graph-based representations of the collaborative filtering space are presented and these are used to define some of the user features as well as being used in a recommendation task.