Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

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Bibliographic Details

Title: Statistical Language Learning
Publisher: MIT Press
Publication Date: 1994
Language: English
ISBN 10: 0262032163
ISBN 13: 9780262032162
Binding: Hardcover
Condition: Good
Weight: 0.974 pounds

About this title

Synopsis

Eugene Charniak breaks new ground in artificial intelligenceresearch by presentingstatistical language processing from an artificial intelligence point of view in a text forresearchers and scientists with a traditional computer science background.New, exacting empiricalmethods 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 languageprocessing techniques ;word tagging, parsing with probabilistic context free grammars, grammarinduction, syntactic disambiguation, semantic wordclasses, word-sense disambiguation ;along with theunderlying mathematics and chapter exercises.Charniak points out that as a method of attacking NLPproblems, the statistical approach has several advantages. It is grounded in real text and thereforepromises to produce usable results, and it offers an obvious way to approach learning: "one simplygathers statistics."Language, Speech, and Communication

About the Author

Eugene Charniak is Professor and Chairman, Department of Computer Science, Brown University.

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