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Integrating Text Retrieval and Image Retrieval in XML Document Searching

  • D. Tjondronegoro
  • J. Zhang
  • J. Gu
  • A. Nguyen
  • S. Geva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3977)

Abstract

Many XML documents contain a mixture of text and images. Images play an important role in webpage or article presentation. However, popular Information Retrieval systems still largely depend on pure text retrieval as it is believed that text descriptions including body text and the caption of images contain precise information. On the other hand, images are more attractive and easier to understand than pure text. We assume that if the image content is used in addition to the pure text-based retrieval, the retrieval result should be better than text-only or image-only retrieval. We test this hypothesis by doing a series of experiments using the Lonely Planet XML document collection. Two search engines, an XML document search engine using both content and structure based on text, and a content-based image search engine were used at the same time. The results generated by these two search engines were merged together to form a new result. This paper presents our current work, initial results and vision into future work.

Keywords

Search Engine Image Retrieval Query Term Retrieval Result Relevance Score 
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 2006

Authors and Affiliations

  • D. Tjondronegoro
    • 1
  • J. Zhang
    • 1
  • J. Gu
    • 1
  • A. Nguyen
    • 1
  • S. Geva
    • 1
  1. 1.Queensland University of TechnologyBrisbaneAustralia

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