Items related to Statistical Language Learning (Language, Speech, and...
Synopsis
Eugene Charniak breaks new ground in artificial intelligence research by presenting statistical language processing from an artificial intelligence point of view in a text for researchers and scientists with a traditional computer science background. New, exacting empirical methods are needed to break the deadlock in such areas of artificial intelligence as robotics, knowledge representation, machine learning, machine translation, and natural language processing (NLP). It is time, Charniak observes, to switch paradigms. This text introduces statistical language processing techniques; word tagging, parsing with probabilistic context free grammars, grammar induction, syntactic disambiguation, semantic wordclasses, word-sense disambiguation; along with the underlying mathematics and chapter exercises. Charniak points out that as a method of attacking NLP problems, the statistical approach has several advantages. It is grounded in real text and therefore promises to produce usable results, and it offers an obvious way to approach learning: "one simply gathers statistics."
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About the Author
Eugene Charniak is Professor of Computer Science at Brown University. He is the author of Statistical Language Learning (MIT Press) and other books.
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- PublisherMIT Press
- Publication date1996
- ISBN 10 0262531410
- ISBN 13 9780262531412
- BindingPaperback
- LanguageEnglish
- Number of pages190
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Statistical Language Learning
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Statistical Language Learning (Language, Speech, and Communication)
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Statistical Language Learning (Language, Speech & Communication)
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Statistical Language Learning (Language, Speech, and Communication)
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Statistical Language Learning (Language, Speech, and Communication) (Language, Speech and Communication Series)
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