Use of implicit graph for recommending relevant videos: a simulated evaluation

  • Authors:

  • David Vallet;Frank Hopfgartner;Joemon Jose

  • Affiliations:

  • Universidad Autónoma de Madrid, Madrid, Spain and University of Glasgow, Glasgow, UK;University of Glasgow, Glasgow, UK;University of Glasgow, Glasgow, UK

  • Venue:
  • ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
  • Year:
  • 2008

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Abstract

In this paper, we propose a model for exploiting community based usage information for video retrieval. Implicit usage information from a pool of past users could be a valuable source to address the difficulties caused due to the semantic gap problem. We propose a graph-based implicit feedback model in which all the usage information can be represented. A number of recommendation algorithms were suggested and experimented. A simulated user evaluation is conducted on the TREC VID collection and the results are presented. Analyzing the results we found some common characteristics on the best performing algorithms, which could indicate the best way of exploiting this type of usage information.