Diversity, Assortment, Dissimilarity, Variety: A Study of Diversity Measures Using Low Level Features for Video Retrieval

  • Martin Halvey
  • P. Punitha
  • David Hannah
  • Robert Villa
  • Frank Hopfgartner
  • Anuj Goyal
  • Joemon M. Jose
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5478)

Abstract

In this paper we present a number of methods for re-ranking video search results in order to introduce diversity into the set of search results. The usefulness of these approaches is evaluated in comparison with similarity based measures, for the TRECVID 2007 collection and tasks [11]. For the MAP of the search results we find that some of our approaches perform as well as similarity based methods. We also find that some of these results can improve the P@N values for some of the lower N values. The most successful of these approaches was then implemented in an interactive search system for the TRECVID 2008 interactive search tasks. The responses from the users indicate that they find the more diverse search results extremely useful.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Martin Halvey
    • 1
  • P. Punitha
    • 1
  • David Hannah
    • 1
  • Robert Villa
    • 1
  • Frank Hopfgartner
    • 1
  • Anuj Goyal
    • 1
  • Joemon M. Jose
    • 1
  1. 1.Department of Computing ScienceUniversity of GlasgowGlasgowScotland

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