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[Association for Computational Linguistics the 37th annual meeting of the Association for Computational Linguistics - College Park, Maryland (1999.06.20-1999.06.26)] Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics - - Supervised grammar induction using training data with limited constituent information

โœ Scribed by Hwa, Rebecca


Book ID
121837265
Publisher
Association for Computational Linguistics
Year
1999
Weight
662 KB
Category
Article

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๐Ÿ“œ SIMILAR VOLUMES


[Association for Computational Linguisti
โœ Hwa, Rebecca ๐Ÿ“‚ Article ๐Ÿ“… 1999 ๐Ÿ› Association for Computational Linguistics โš– 662 KB

Corpus-based grammar induction generally relies on hand-parsed training data to learn the structure of the language. Unfortunately, the cost of building large annotated corpora is prohibitively expensive. This work aims to improve the induction strategy when there are few labels in the training data

[Association for Computational Linguisti
โœ Chen, Stanley F. ๐Ÿ“‚ Article ๐Ÿ“… 1995 ๐Ÿ› Association for Computational Linguistics โš– 639 KB

We describe a corpus-based induction algorithm for probabilistic context-free grammars. The algorithm employs a greedy heuristic search within a Bayesian framework, and a post-pass using the Inside-Outside algorithm. We compare the performance of our algorithm to n-gram models and the Inside-Outside