The acquisition of syntactic knowledge
The acquisition of syntactic knowledge
Theory of Syntactic Recognition for Natural Languages
Theory of Syntactic Recognition for Natural Languages
How to detect grammatical errors in a text without parsing it
EACL '87 Proceedings of the third conference on European chapter of the Association for Computational Linguistics
Towards a dictionary support environment for real time parsing
EACL '85 Proceedings of the second conference on European chapter of the Association for Computational Linguistics
How to detect grammatical errors in a text without parsing it
EACL '87 Proceedings of the third conference on European chapter of the Association for Computational Linguistics
Syntactic pattern recognition from observations: a hybrid technique
ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
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Within computational linguistics, the use of statistical pattern matching is generally restricted to speech processing. We have attempted to apply statistical techniques to discover a grammatical classification system from a Corpus of 'raw' English text. A discovery procedure is simpler for a simpler language model; we assume a first-order Markov model, which (surprisingly) is shown elsewhere to be sufficient for practical applications. The extraction of the parameters of a standard Markov model is theoretically straightforward; however, the huge size of the standard model for a Natural Language renders it incomputable in reasonable time. We have explored various constrained models to reduce computation, which have yielded results of varying success.