XML Information Retrieval through Tree Edit Distance and Structural Summaries

  • Cyril Laitang
  • Mohand Boughanem
  • Karen Pinel-Sauvagnat
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7097)


Semi-structured Information Retrieval (SIR) allows the user to narrow his search down to the element level. As queries and XML documents can be seen as hierarchically nested elements, we consider that their structural proximity can be evaluated through their trees similarity. Our approach combines both content and structure scores, the latter being based on tree edit distance (minimal cost of operations to turn one tree to another). We use the tree structure to propagate and combine both measures. Moreover, to overcome time and space complexity, we summarize the document tree structure. We experimented various tree summary techniques as well as our original model using the SSCAS task of the INEX 2005 campaign. Results showed that our approach outperforms state of the art ones.


Edit Distance Vector Space Model Tree Match Virtual Edge Structure 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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© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Cyril Laitang
    • 1
  • Mohand Boughanem
    • 1
  • Karen Pinel-Sauvagnat
    • 1
  1. 1.IRIT-SIGToulouseFrance

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