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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. (Update)
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BibTeX entry: (Update)
@misc{ annotated-learning,
author = "From Completely Annotated",
title = "Learning Node Selecting Tree Transducer",
url = "citeseer.ist.psu.edu/706581.html" }
Citations (may not include all citations):33 Visual web information extraction with lixto - Baumgartner, Flesca et al. - 2001
5 Wrapping web information providers by transducer induction - Chidlovskii - 2001
4 A flexible learning system for wrapping (context) - Cohen, Hurst et al.
3 Querying unranked trees with stepwise tree automata (context) - Carme, Niehren et al. - 2004
2 Learning regular node queries in trees from completely annot.. (context) - Carme, Lemay et al. - 2004
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