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Published Articles >> Table of Contents >> Abstract
20th International Conference on Data Engineering (ICDE'04)
p. 276
A Machine Learning Approach to Rapid Development of XML Mapping Queries
Atsuyuki Morishima, University of Tsukuba
Hiroyuki Kitagawa, University of Tsukuba
Akira Matsumoto, University of Tsukuba
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDE.2004.1320004
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This paper presents XLearner, a novel tool that helps the rapid development of XML mapping queries written in XQuery. XLearner is novel in that it learns XQuery queries consistent with given examples (fragments) of intended query results. XLearner combines known learning techniques, incorporates mechanisms to cope with issues specific to the XQuery learning context, and provides a systematic way for the semi-automatic development of queries. This paper describes the XLearner system. It presents algorithms for learning various classes of XQuery, shows that a minor extension gives the system a practical expressive power, and reports experimental results to demonstrate how XLearner outputs reasonably complicated queries with only a small number of interactions with the user.
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Citation:
Atsuyuki Morishima, Hiroyuki Kitagawa, Akira Matsumoto,
"A Machine Learning Approach to Rapid Development of XML Mapping Queries,"
icde,
p. 276,
20th International Conference on Data Engineering (ICDE'04),
2004
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