SPECIAL ISSUE: Personalization Techniques and Recommender Systems; Edited by G. Uchyigit and M. Y. MaNo Access

IDENTIFYING USER AND GROUP INFORMATION FROM COLLABORATIVE FILTERING DATASETS

JOSEPHINE GRIFFITH

Department of Information Technology, National University of Ireland, Galway, Ireland

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COLM O'RIORDAN

Department of Information Technology, National University of Ireland, Galway, Ireland

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, and

HUMPHREY SORENSEN

Department of Computer Science, University College Cork, Ireland

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https://doi.org/10.1142/S0218001407005405Cited by:1 (Source: Crossref)

Abstract

This paper considers the information that can be captured about users and groups 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 and group 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 and group features as well as being used in a recommendation task.

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