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pro vyhledávání: '"Brill, Eric"'
We describe an investigation of the use of probabilistic models and cost-benefit analyses to guide resource-intensive procedures used by a Web-based question answering system. We first provide an overview of research on question-answering systems. Th
Externí odkaz:
http://arxiv.org/abs/1212.2453
Autor:
Brill, Eric, Ngai, Grace
Publikováno v:
Proceedings of the 37th Annual Meeting of the Association of Computational Linguistics, pages 65-72, College Park, MD, USA (1999)
A great deal of work has been done demonstrating the ability of machine learning algorithms to automatically extract linguistic knowledge from annotated corpora. Very little work has gone into quantifying the difference in ability at this task betwee
Externí odkaz:
http://arxiv.org/abs/cs/0105002
Autor:
Henderson, John C., Brill, Eric
Publikováno v:
Proceedings of the 1st Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL-2000), pages 34-41
Bagging and boosting, two effective machine learning techniques, are applied to natural language parsing. Experiments using these techniques with a trainable statistical parser are described. The best resulting system provides roughly as large of a g
Externí odkaz:
http://arxiv.org/abs/cs/0006011
Autor:
Henderson, John C., Brill, Eric
Publikováno v:
Proceedings of the Fourth Conference on Empirical Methods in Natural Language Processing (EMNLP-99), pages 187-194. College Park, Maryland, USA. June, 1999
Three state-of-the-art statistical parsers are combined to produce more accurate parses, as well as new bounds on achievable Treebank parsing accuracy. Two general approaches are presented and two combination techniques are described for each approac
Externí odkaz:
http://arxiv.org/abs/cs/0006003
Autor:
Brill, Eric, Resnik, Philip
Publikováno v:
COLING 1994
In this paper, we describe a new corpus-based approach to prepositional phrase attachment disambiguation, and present results comparing performance of this algorithm with other corpus-based approaches to this problem.
Comment: 7 pages, compresse
Comment: 7 pages, compresse
Externí odkaz:
http://arxiv.org/abs/cmp-lg/9410026
Autor:
Brill, Eric
Publikováno v:
Proceedings of AAAI94
Most recent research in trainable part of speech taggers has explored stochastic tagging. While these taggers obtain high accuracy, linguistic information is captured indirectly, typically in tens of thousands of lexical and contextual probabilities.
Externí odkaz:
http://arxiv.org/abs/cmp-lg/9406010
Autor:
Brill, Eric ericdbrill@gmail.com
Publikováno v:
Public Contract Law Journal. Summer2021, Vol. 50 Issue 4, p623-641. 19p.
Autor:
Jones, Karen Spärck, Kempen, Gerard A. M, Resnik, Philip, Brill, Eric, Shieber, Stuart M, Perrault, C. Raymond, Schubert, Lenhart K, Klavans, Judith
Publikováno v:
International Encyclopedia of Linguistics, 2 ed., 2003, ill.
Externí odkaz:
http://www.oxfordreference.com/view/10.1093/acref/9780195139778.001.0001/acref-9780195139778-e-0218
Publikováno v:
In Information Processing and Management 2004 40(5):849-868
Publikováno v:
In Computer Speech & Language October 2000 14(4):373-400