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An Adaptable and Adjustable Mapping from XML Data to Tables in RDB

  • Wang Xiao-ling
  • Luan Jin-feng
  • Dong Yi-sheng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2590)

Abstract

The purpose of this paper is to present the results of an initial study about automatically storing XML data in RDBMS. These are some research about storing given XML data, and most of these approaches based on pre-defined rules and heuristics, without considering application requirement and workload. As the result, the relational schema obtained for given XML is often not optimal for query performance. As a first step, this study was focused on providing an adaptable and adjustable strategy for modelling XML data in relational database systems. This AAM (Adjustable and Adaptable Method) takes advantage of the GA (Genetic Algorithm) to design data schema in RDBMS based on cost-driven approach, we implement and evaluate our approach. Experiments show that this method provides an adaptable and automatic mapping from XML data to physical tables in RDBMS with respect to different users and application requirement.

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References

  1. [1]
    F. Tian, D. J. DeWitt, J.j. Chen and C. Zhang. The Design and Performance Evaluation of Alternative XML Storage Strategies. Technical report, CS Dept., Universiy of Wisconsin, 2000. Available at http://www.cs.wisc.edu/niagara/papers/vldb00XML.pdf.
  2. [2]
    D. Florescu, D. Kossmann. Storing and Querying XML Data using an RDMBS. Data Engineering, September 1999 Vol. 22 No. 3. p27–34.Google Scholar
  3. [3]
    A. Deutsch, M. Fernandez, and D. Suciu. Storing semistructured data with STORED. In Proc. of ACM SIGMOD, Philadelphia, PN, 1999.Google Scholar
  4. [4]
    K. Wang and H.q. Liu. Discovering typical structures of documents: a road map approach. In ACM SIGIR Conferences on Research and Development in Information Retrieval, August 1998.Google Scholar
  5. [5]
    R. Q. Lu, J. Zhi, G. Chen, Ontology-oriented Requirement Analysis, Journal of Software, 2000,11(8).Google Scholar
  6. [6]
    Kenneth De Jong. Evolving in a changing world. International Workshop on Evolutionary Computation. April, 2000.Google Scholar
  7. [7]
    J. H. Holland. Adaptation in Natural and Artifical Systems. University of Michigan Press. Ann Arbor, MI, 1975.Google Scholar
  8. [8]
    D. Florescu and D. Kossmann. A performance evaluation of alternative mapping schemes for storing XML data in a relational database. Technical Report, INRIA, France, 1999.Google Scholar
  9. [9]
    J. Shanmugasundaram et al. Relational databases for querying XML documents: Limitations and opportunities. In Proc. of VLDB, Edinburgh, Scotland, 1999.Google Scholar
  10. [11]
    Abiteboul, S., Quass, D., McHugh, J., Widom, J. and Wiener, J. The Lorel query language for semistructured data. International Journal on Digital Libraries, 1(1):68–88, April 1997.CrossRefGoogle Scholar
  11. [12]
    Roy, G., Narayanan, S., Suresh, V. and Hector, G. Proximity Search in Databases. In Proceedings of the 24th VLDB Conference, 1998.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Wang Xiao-ling
    • 1
  • Luan Jin-feng
    • 1
  • Dong Yi-sheng
    • 1
  1. 1.Southeast UniversityNanjingChina

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