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Vector Retrieval Model for XML Document Based on Dynamic Partition of Information Units

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3528))

Abstract

XML document is applied in WEB application more and more. Because users can find what they need in numerous XML documents, technology of information retrieval based on XML document becomes a hot topic in information retrieval field now. Traditional technology of information retrieval based on XML document need define retrieval unit and retrieval result unit of the retrieval beforehand, and the dividing granularity is either too big or too small. In this paper we propose a retrieval method, which can dynamically partition information units in terms of the structure and semantic information of XML in vector space model. Therefore it reduces calculating workload efficiently and improves running efficiency of the entire retrieval system. The retrieval efficiency of this method is proved than the traditional one when they have the same accuracy. Finally, the results have been testified by experiment.

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References

  1. Salton, G., Wong, A.: A vector space model for automatic indexing. Communications of the ACM 18, 613–620 (1975)

    Article  MATH  Google Scholar 

  2. Lee, J.: Analyzig the Effectiveness of Extended Boolean Models in Information Retrieval. In: Proc. of SIGIR 1994, Dublin, Ireland, pp. 182–190 (1994)

    Google Scholar 

  3. Theobald, A., Weikem, G.: Adding relevance to XML. In: Suciu, D., Vossen, G. (eds.) WebDB 2000. LNCS, vol. 1997, pp. 105–124. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  4. Fuhr, N., Grobjohann, K.: XIRQL: A query language for information retrieval in XML documents. In: Proceedings of the 24th Annual International Conference on Research and development in Information Retrieval, New Orleans, USA, pp. 172–180 (2001)

    Google Scholar 

  5. Hayashi, Y., Tomita, J.: Searching text-rich XML documents with relevance ranking. In: ACM SIGIR 2000 Workshop on XML and Information Retrieval, Athens, Greece (2000)

    Google Scholar 

  6. Hatano, K., Kinutani, H., Yoshikawa, M., Uemura, S.: Information Retrieval System for XML Documents. In: Hameurlain, A., Cicchetti, R., Traunmüller, R. (eds.) DEXA 2002. LNCS, vol. 2453, pp. 758–767. Springer, Heidelberg (2002)

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© 2005 Springer-Verlag Berlin Heidelberg

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Cui, Lz., Wang, Hy. (2005). Vector Retrieval Model for XML Document Based on Dynamic Partition of Information Units. In: Szczepaniak, P.S., Kacprzyk, J., Niewiadomski, A. (eds) Advances in Web Intelligence. AWIC 2005. Lecture Notes in Computer Science(), vol 3528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11495772_19

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  • DOI: https://doi.org/10.1007/11495772_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26219-0

  • Online ISBN: 978-3-540-31900-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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