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pro vyhledávání: '"Wide R. Hogenhout"'
Autor:
Yuji Matsumoto, Wide R. Hogenhout
Publikováno v:
Natural Language Engineering. 4:191-209
The statistical induction of stochastic context free grammars from bracketed corpora with the Inside Outside Algorithm is an appealing method for grammar learning, but the computational complexity of this algorithm has made it impossible to generate
Autor:
Wide R. Hogenhout, Yuji Matsumoto
Publikováno v:
Journal of Natural Language Processing. 5:25-46
We show how a treebank can be used to cluster words on the basis of their syntactic behavior. By extracting statistics on the structures in which words appear it is possible to discover similarities and differences in usage between words with the sam
Autor:
Yuji Matsumoto, Wide R. Hogenhout
Publikováno v:
Proceedings of the International Workshop on Finite State Methods in Natural Language Processing - FSMNLP '09.
Recent approaches to statistical parsing include those that estimate an approximation of a stochastic, lexicalized grammar directly from a treebank and others that rebuild trees with a number of tree-constructing operators, which are applied in order
Autor:
Yuji Matsumoto, Wide R. Hogenhout
Publikováno v:
COLING
Since treebanks have become available to researchers a wide variety of techniques has been used to make broad coverage parsing systems. This makes quantitative evaluation very important, but the current evaluation methods have a number of drawbacks s