Feedback-Driven Structural Query Expansion for Ranked Retrieval of XML Data

  • Ralf Schenkel
  • Martin Theobald
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3896)


Relevance Feedback is an important way to enhance retrieval quality by integrating relevance information provided by a user. In XML retrieval, feedback engines usually generate an expanded query from the content of elements marked as relevant or nonrelevant. This approach that is inspired by text-based IR completely ignores the semistructured nature of XML. This paper makes the important step from content-based to structural feedback. It presents an integrated solution for expanding keyword queries with new content, path, and document constraints. An extensible framework evaluates such query conditions with existing keyword-based XML search engines while allowing to easily integrate new dimensions of feedback. Extensive experiments with the established INEX benchmark show the feasibility of our approach.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ralf Schenkel
    • 1
  • Martin Theobald
    • 1
  1. 1.Max-Planck-Institut für InformatikSaarbrückenGermany

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