Evaluation of Diversity-Focused Strategies for Multimedia Retrieval

  • Julien Ah-Pine
  • Gabriela Csurka
  • Jean-Michel Renders
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5706)


In this paper, we propose and evaluate different strategies to promote diversity in the top results of multimedia retrieval systems. These strategies consist in clustering, explicitly or implictly, the elements of the top list of some initial ranking and produce a re-ranking that favours elements belonging to different clusters. We evaluate these strategies in the particular case of ImageCLEFPhoto 2008 Collection. Results show that most of these strategies succeed in increasing a diversity performance measure, while keeping or slightly degrading precision of the top list and, more interestingly, they achieve this in complementary ways.


Query Image Multimedia Retrieval Basic Ranking Sport Stadium Ground Truth Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Julien Ah-Pine
    • 1
  • Gabriela Csurka
    • 1
  • Jean-Michel Renders
    • 1
  1. 1.Xerox Research Centre EuropeMeylanFrance

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