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Unsupervised Models for Named Entity Classification (1999)

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by Michael Collins , Yoram Singer
Venue:In Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora
Citations:541 - 4 self
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Citations

11956 Maximum Likelihood from Incomplete Data via the EM Algorithm - Dempster, Laird, et al. - 1997
3495 Schapire, “A decision-theoretic generalization of on-line learning and an application to boosting - Freund, E - 1997
1984 A theory of the learnable - Valiant - 1984
1632 Combining labeled and unlabeled data with cotraining - BLUM, MITCHELL - 1998
1261 Automatic acquisition of hyponyms from large text corpora. - Hearst - 1992
938 Improved boosting algorithms using confidence-rated predictions - Schapire, Singer - 1999
868 The strength of weak learnability - Schapire - 1990
490 A New Statistical Parser Based on Bigram Lexical Dependencies. - Collins - 1996
471 Extracting patterns and relations from the World Wide Web, in: - Brin - 1998
378 Learning Dictionaries for Information Extraction by Multi-level Boot-strapping. - Riloff, Jones - 1999
326 Nymble: a High-Performance Learning Name-finder,” - Bikel, Miller, et al. - 1997
277 Finding parts in very large corpora. - Berland, Charniak - 1999
136 A corpus-based approach for building semantic lexicons - Riloff, Shepherd - 1997
130 Unsupervised learning of disambiguation rules for part of speech tagging - Brill - 1995
41 Additive models, boosting and inference for generalized divergences. - Lafferty - 1999
12 Thoughts on hypothesis boosting": Unpublished manuscript [Online] available: http://www.citeulike.org/user/seb1/article/5980850 - Kearns - 1988
4 A New Statistical Parser Based on Bigram - Collins - 1996
2 A decision-theoretic generalization of on-line learning and an application to boosting - Information, Computation - 1995
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