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Community based feedback techniques to improve video search

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Abstract

In this paper, we present a novel approach to aid users in the difficult task of video search. We use a graph based model based on implicit feedback mined from the interactions of previous users of our video search system to provide recommendations to aid users in their search tasks. This approach means that users are not burdened with providing explicit feedback, while still getting the benefits of recommendations. The goal of this approach is to improve the quality of the results that users find, and in doing so also help users to explore a large and difficult information space. In particular we wish to make the challenging task of video search much easier for users. The results of our evaluation indicate that we achieved our goals, the performance of the users in retrieving relevant videos improved, and users were able to explore the collection to a greater extent.

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Authors and Affiliations

  1. Universidad Autónoma de Madrid, Escuela Politécnica Superior Ciudad Universitaria de Cantoblanco, 28049, Madrid, Spain

    David Vallet

  2. Department of Computing Science, University of Glasgow, Glasgow, G12 8QQ, UK

    Frank Hopfgartner, Martin Halvey & Joemon M. Jose

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  1. David Vallet
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  2. Frank Hopfgartner
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  3. Martin Halvey
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  4. Joemon M. Jose
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Correspondence to David Vallet.

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Vallet, D., Hopfgartner, F., Halvey, M. et al. Community based feedback techniques to improve video search. SIViP 2, 289–306 (2008). https://doi.org/10.1007/s11760-008-0087-y

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  • DOI: https://doi.org/10.1007/s11760-008-0087-y

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