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Feature-based and Clique-based User Models for Movie Selection: A Comparative Study

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Abstract

The huge amount of information available in the currently evolving world wide information infrastructure at any one time can easily overwhelm end-users. One way to address the information explosion is to use an ‘information filtering agent’ which can select information according to the interest and/or need of an end-user. However, at present few information filtering agents exist for the evolving world wide multimedia information infrastructure. In this study, we evaluate the use of feature-based approaches to user modeling with the purpose of creating a filtering agent for the video-on-demand application. We evaluate several feature and clique-based models for 10 voluntary subjects who provided ratings for the movies. Our preliminary results suggest that feature-based selection can be a useful tool to recommend movies according to the taste of the user and can be as effective as a movie rating expert. We compare our feature-based approach with a clique-based approach, which has advantages where information from other users is available.

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Authors and Affiliations

  1. ECE Department, University of Colorado, Colorado Springs, Colorado, 90918, U.S.A.

    Joshua Alspector & Aleksander Koicz

  2. IF-319B, Bellcore, 445 South Street, Morristown, NJ, 07960

    N. Karunanithi

Authors
  1. Joshua Alspector
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  2. Aleksander Koicz
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  3. N. Karunanithi
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Alspector, J., Koicz, A. & Karunanithi, N. Feature-based and Clique-based User Models for Movie Selection: A Comparative Study. User Modeling and User-Adapted Interaction 7, 279–304 (1997). https://doi.org/10.1023/A:1008286413827

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  • DOI: https://doi.org/10.1023/A:1008286413827

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