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Term Statistics for Structured Text Retrieval

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Encyclopedia of Database Systems

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Synonyms

Within-element term frequency; Inverse element frequency

Definition

Classical ranking algorithms in information retrieval make use of term statistics, the most common (and basic) ones being within-document term frequency, tf, and document frequency, df. tf is the number of occurrences of a term in a document and is used to reflect how well a term captures the topic of a document, whereas df is the number of documents in which a term appears and is used to reflect how well a term discriminates between relevant and non-relevant documents. df is also commonly referred to as inverse document frequency, idf, since it is inversely related to the importance of a term. Both tf and idf are obtained at indexing time. Ranking algorithms for structured text retrieval, and more precisely XML retrieval, require similar terms statistics, but with respect to elements.

Key Points

To calculate term statistics for elements, one could simply replace documents by elements and calculate so-called...

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Recommended Reading

  1. Clarke C.L.A. Controlling overlap in content-oriented XML retrieval. In Proc. 31st Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, 2005, pp. 441–448.

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  2. Grabs G. and Schek H.-S. ETH Zürich at INEX: flexible information retrieval from XML with PowerDB-XML. In Proc. 1st Int. Workshop of the Initiative for the Evaluation of XML Retrieval, 2002, pp. 141–148.

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  3. Mass Y. and Mandelbrod M. Component ranking and automatic query refinement for XML retrieval. In Proc. 4th Int. Workshop of the Initiative for the Evaluation of XML Retrieval, 2005, pp. 73–84.

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  4. Sigurbjörnsson B., Kamps J., and de Rijke M. An element-based approach to XML retrieval. In Proc. 2nd Int. Workshop of the Initiative for the Evaluation of XML Retrieval, 2003, pp. 19–26.

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Author information

Authors and Affiliations

    Authors
    1. Mounia Lalmas
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    Editor information

    Editors and Affiliations

    1. College of Computing, Georgia Institute of Technology, 266 Ferst Drive, 30332-0765, Atlanta, GA, USA

      LING LIU (Professor) (Professor)

    2. Database Research Group David R. Cheriton School of Computer Science, University of Waterloo, 200 University Avenue West, N2L 3G1, Waterloo, ON, Canada

      M. TAMER ÖZSU (Professor and Director, University Research Chair) (Professor and Director, University Research Chair)

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    © 2009 Springer Science+Business Media, LLC

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    Lalmas, M. (2009). Term Statistics for Structured Text Retrieval. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_412

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