Relevant Clouds: Leveraging Relevance Feedback to Build Tag Clouds for Image Search

  • Luis A. Leiva
  • Mauricio Villegas
  • Roberto Paredes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8138)


Previous work in the literature has been aimed at exploring tag clouds to improve image search and potentially increase retrieval performance. However, to date none has considered the idea of building tag clouds derived from relevance feedback. We propose a simple approach to such an idea, where the tag cloud gives more importance to the words from the relevant images than the non-relevant ones. A preliminary study with 164 queries inspected by 14 participants over a 30M dataset of automatically annotated images showed that 1) tag clouds derived this way are found to be informative: users considered roughly 20% of the presented tags to be relevant for any query at any time; and 2) the importance given to the tags correlates with user judgments: tags ranked in the first positions tended to be perceived more often as relevant to the topic that users had in mind.


Image Search and Retrieval Relevance Feedback Tag Clouds 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Luis A. Leiva
    • 1
  • Mauricio Villegas
    • 1
  • Roberto Paredes
    • 1
  1. 1.ITI/DSICUniversitat Politècnica de ValènciaSpain

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