Co-active intelligence for image retrieval

  • Authors:
  • Mark Truran;James Goulding;Helen Ashman

  • Affiliations:
  • University of Nottingham, Nottingham, United Kingdom;University of Nottingham, Nottingham, United Kingdom;University of Nottingham, Nottingham, United Kingdom

  • Venue:
  • Proceedings of the 13th annual ACM international conference on Multimedia
  • Year:
  • 2005

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Abstract

Lexical ambiguity in query-based image retrieval is an immemorial problem which has seemingly resisted all countermeasures. In this paper we introduce a methodology that expresses the users of a system and their navigational behaviour as the paramount resource for resolving query term ambiguity. Mass user consensus is modelled within a multi-dimensional feature space and evaluated through cluster analysis. This technique resolves query term ambiguity in a wholly democratic and dynamic fashion, in contrast to the brittle centralised models of contemporary word sense classification systems. The simple approach contained herein leads to several interesting emergent properties.