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DTD Based Costs for Tree-Edit Distance in Structured Information Retrieval

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Advances in Information Retrieval (ECIR 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7814))

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Abstract

In this paper we present a Structured Information Retrieval (SIR) model based on graph matching. Our approach combines content propagation, which handles sibling relationships, with a document-query structure matching process. The latter is based on Tree-Edit Distance (TED) which is the minimum set of insert, delete, and replace operations to turn one tree to another. To our knowledge this algorithm has never been used in ad-hoc SIR. As the effectiveness of TED relies both on the input tree and the edit costs, we first present a focused subtree extraction technique which selects the most representative elements of the document w.r.t the query. We then describe our TED costs setting based on the Document Type Definition (DTD). Finally we discuss our results according to the type of the collection (data-oriented or text-oriented). Experiments are conducted on two INEX test sets: the 2010 Datacentric collection and the 2005 Ad-hoc one.

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Author information

Authors and Affiliations

  1. IRIT-SIG, 118 route de Narbonne, 31062, Toulouse Cedex 9, France

    Cyril Laitang, Karen Pinel-Sauvagnat & Mohand Boughanem

Authors
  1. Cyril Laitang
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  2. Karen Pinel-Sauvagnat
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  3. Mohand Boughanem
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Editor information

Editors and Affiliations

  1. Yandex, Leo Tolstoy, 16, 119021, Moscow, Russia

    Pavel Serdyukov  & Ilya Segalovich  & 

  2. Kontur Labs and Ural Federal University, Fonvizina 3-27, 620078, Yekaterinburg, Russia

    Pavel Braslavski

  3. National Research University Higher School of Economics (HSE), Pokrovskii bd 11, 109028, Moscow, Russia

    Sergei O. Kuznetsov

  4. University of Amsterdam, Turfdraagsterpad 9, 1012 XT, Amsterdam, The Netherlands

    Jaap Kamps

  5. Knowledge Media Institute, The Open University, Walton Hall, MK7 6AA, Milton Keynes, UK

    Stefan Rüger

  6. Mathematics & Computer Science Department, Emory University, 400 dowman Drive, 30329, Atlanta, GA, USA

    Eugene Agichtein

  7. Department of Computer Science, University College London, Gower Street, WC1E 6BT, London, UK

    Emine Yilmaz

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Laitang, C., Pinel-Sauvagnat, K., Boughanem, M. (2013). DTD Based Costs for Tree-Edit Distance in Structured Information Retrieval. In: Serdyukov, P., et al. Advances in Information Retrieval. ECIR 2013. Lecture Notes in Computer Science, vol 7814. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36973-5_14

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  • DOI: https://doi.org/10.1007/978-3-642-36973-5_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36972-8

  • Online ISBN: 978-3-642-36973-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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