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ICGI
2004
Springer

Learning Node Selecting Tree Transducer from Completely Annotated Examples

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Learning Node Selecting Tree Transducer from Completely Annotated Examples
Abstract. A base problem in Web information extraction is to find appropriate queries for informative nodes in trees. We propose to learn queries for nodes in trees automatically from examples. We introduce node selecting tree transducer (NSTT) and show how to induce deterministic NSTTs in polynomial time from completely annotated examples. We have implemented learning algorithms for NSTTs, started applying them to Web information extraction, and present first experimental results.
Julien Carme, Aurélien Lemay, Joachim Niehr
Added 01 Jul 2010
Updated 01 Jul 2010
Type Conference
Year 2004
Where ICGI
Authors Julien Carme, Aurélien Lemay, Joachim Niehren
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