A Machine Learning Approach to Rapid Development of XML Mapping Queries

  • Authors:
  • Atsuyuki Morishima;Hiroyuki Kitagawa;Akira Matsumoto

  • Affiliations:
  • -;-;-

  • Venue:
  • ICDE '04 Proceedings of the 20th International Conference on Data Engineering
  • Year:
  • 2004

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Abstract

This paper presents XLearner, a novel tool that helpsthe rapid development of XML mapping queries writtenin XQuery. XLearner is novel in that it learns XQueryqueries consistent with given examples (fragments) of intendedquery results. XLearner combines known learningtechniques, incorporates mechanisms to cope with issuesspecific to the XQuery learning context, and provides a systematicway for the semi-automatic development of queries.This paper describes the XLearner system. It presents algorithmsfor learning various classes of XQuery, shows thata minor extension gives the system a practical expressivepower, and reports experimental results to demonstrate howXLearner outputs reasonably complicated queries with onlya small number of interactions with the user.