The potential of user feedback through the iterative refining of queries in an image retrieval system

Authors:
Maher Ben Moussa;Marco Pasch;Djoerd Hiemstra;Paul Van Der Vet;Theo Huibers
Affiliations:
University of Twente, Enschede, The Netherlands;University of Twente, Enschede, The Netherlands;University of Twente, Enschede, The Netherlands;University of Twente, Enschede, The Netherlands;University of Twente, Enschede, The Netherlands
Venue:
AMR'06 Proceedings of the 4th international conference on Adaptive multimedia retrieval: user, context, and feedback
Year:
2006

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Abstract

Inaccurate or ambiguous expressions in queries lead to poor results in information retrieval. We assume that iterative user feedback can improve the quality of queries. To this end we developed a system for image retrieval that utilizes user feedback to refine the user's search query. This is done by a graphical user interface that returns categories of images and requires the user to choose between them in order to improve the initial query in terms of accuracy and unambiguousness. A user test showed that, although there was no improvement in search time or required search restarts, iterative user feedback can indeed improve the performance of an image retrieval system in terms of user satisfaction.