A statistical approach to machine translation
Computational Linguistics
Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
Making large-scale support vector machine learning practical
Advances in kernel methods
Three machine learning algorithms for lexical ambiguity resolution
Three machine learning algorithms for lexical ambiguity resolution
Automatic word sense discrimination
Computational Linguistics - Special issue on word sense disambiguation
Distribution of content words and phrases in text and language modelling
Natural Language Engineering
A word-to-word model of translational equivalence
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Minimally supervised induction of grammatical gender
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
HLT '91 Proceedings of the workshop on Speech and Natural Language
Learning subjective nouns using extraction pattern bootstrapping
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
A high-performance semi-supervised learning method for text chunking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Annealing structural bias in multilingual weighted grammar induction
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
The bootstrapping of the Yarowsky algorithm in real corpora
Information Processing and Management: an International Journal
Reducing semantic drift with bagging and distributional similarity
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Bootstrapping via graph propagation
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
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"Bootstrapping" methods for learning require a small amount of supervision to seed the learning process. We show that it is sometimes possible to eliminate this last bit of supervision, by trying many candidate seeds and selecting the one with the most plausible outcome. We discuss such "strapping" methods in general, and exhibit a particular method for strapping word-sense classifiers for ambiguous words. Our experiments on the Canadian Hansards show that our unsupervised technique is significantly more effective than picking seeds by hand (Yarowsky, 1995), which in turn is known to rival supervised methods.