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Abstract: We investigate the application of classification techniques to the problem of information extraction (IE). In particular we use support vector machines and several different feature-sets to build a set of classifiers for IE. We show that this approach is competitive with current state-of-the-art IE algorithms based on specialized learning algorithms. We also introduce a new technique for improving the recall of our IE algorithm. This approach uses a two-level ensemble of classifiers to... (Update)
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BibTeX entry: (Update)
Aidan Finn and Nicholas Kushmerick. Multi-level boundary classification for information extraction. In Proceedings of the European Conference on Machine Learning, Pisa, 2004. http://citeseer.ist.psu.edu/article/finn04multilevel.html More
@misc{ finn04multilevel,
author = "A. Finn and N. Kushmerick",
title = "Multi-level boundary classification for information extraction",
text = "Aidan Finn and Nicholas Kushmerick. Multi-level boundary classification
for information extraction. In Proceedings of the European Conference on
Machine Learning, Pisa, 2004.",
year = "2004",
url = "citeseer.ist.psu.edu/article/finn04multilevel.html" }
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2 A critical survey of the methodology for IE evaluation - Lavelli, Califf et al. - 2004
2 Bayesian information extraction network - Peshkin, Pfeffer - 2003
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