Difference between revisions of "Klein et al, ACL 2002"
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| − | + | In this [[Category::paper]] authors present a generative distributed model for the unsupervised induction of natural language syntax which explicitly models constituents yields and context. Parameter search with EM produces higher quality analysis than previously proposed unsupervised systems. | |
Revision as of 23:06, 1 November 2011
Citation
Dan Klein and Christopher D. Manning. 2002. A generative constituent-context model for improved grammar induction. In Proceedings of the 40th Annual Meeting on Association for Computational Linguistics (ACL '02). Association for Computational Linguistics, Stroudsburg, PA, USA, 128-135.
Online version
http://acl.ldc.upenn.edu/P/P02/P02-1017.pdf
Summary
In this paper authors present a generative distributed model for the unsupervised induction of natural language syntax which explicitly models constituents yields and context. Parameter search with EM produces higher quality analysis than previously proposed unsupervised systems.
