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OverviewThis text presents statistical language processing from an artificial intelligence point of view intended for researchers and scientists with a traditional computer science background. The book argues that 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 introduces statistical language processing techniques - word tagging, parsing with probabilistic context free grammars, grammar induction, syntactic disambiguation, semantic word classes, word-sense disambiguation - along with the underlying mathematics and chapter exercises. The author points out that as a method of attacking NLP problems, the statistical approach has several advantages. It is grounded in real text and therefore produces usable results. Full Product DetailsAuthor: Eugene Charniak (Brown University)Publisher: MIT Press Ltd Imprint: MIT Press Edition: New edition Dimensions: Width: 15.00cm , Height: 1.00cm , Length: 22.40cm Weight: 0.318kg ISBN: 9780262531412ISBN 10: 0262531410 Pages: 190 Publication Date: 26 August 1996 Recommended Age: From 18 to 99 years Audience: College/higher education , Professional and scholarly , Postgraduate, Research & Scholarly , Professional & Vocational Format: Paperback Publisher's Status: Unknown Availability: Awaiting stock Table of ContentsReviewsThis is a lovely book. -- David Nye """This is a lovely book."" -- David Nye" Author InformationEugene Charniak is Professor of Computer Science at Brown University. He is the author of Statistical Language Learning (MIT Press) and other books. Tab Content 6Author Website:Countries AvailableAll regions |