Context-based clustering of image search results

  • Authors:

  • Hongqi Wang;Olana Missura;Thomas Gärtner;Stefan Wrobel

  • Affiliations:

  • Fraunhofer Institute Intelligent Analysis and Information Systems, Sankt Augustin, Germany and Department of Computer Science III, Rheinische Friedrich-Wilhelms-Universitt Bonn, Bonn, Germany;Fraunhofer Institute Intelligent Analysis and Information Systems, Sankt Augustin, Germany;Fraunhofer Institute Intelligent Analysis and Information Systems, Sankt Augustin, Germany;Fraunhofer Institute Intelligent Analysis and Information Systems, Sankt Augustin, Germany and Department of Computer Science III, Rheinische Friedrich-Wilhelms-Universitt Bonn, Bonn, Germany

  • Venue:
  • KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
  • Year:
  • 2009

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Abstract

In this work we propose to cluster image search results based on the textual contents of the referring webpages. The natural ambiguity and context-dependence of human languages lead to problems that plague modern image search engines: A user formulating a query usually has in mind just one topic, while the results produced to satisfy this query may (and usually do) belong to the different topics. Therefore, only part of the search results are relevant for a user. One of the possible ways to improve the user's experience is to cluster the results according to the topics they belong to and present the clustered results to the user. As opposed to the clustering based on visual features, an approach utilising the text information in the webpages containing the image is less computationally intensive and provides the resulting clusters with semantically meaningful names.