Improving Generalization with Active Learning
Machine Learning - Special issue on structured connectionist systems
Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
A novel use of statistical parsing to extract information from text
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
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This paper addresses the problem of efficiently obtaining training data for a new entity type or relation. We describe a methodology for rapidly obtaining annotation by using seed examples and human feedback, and we show that this method allows annotation to be performed approximately 20 times faster than manual annotation alone, with small degradation in annotation accuracy.