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A Machine Learning Approach to Rapid Development of XML Mapping Queries

Authors: 
Morishima, A.; Kitagawa, H.; Matsumoto, A.
Year: 
2004
Venue: 
ICDE 2004

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

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