Hardcover. Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications. An introduction to statistical natural language processing (NLP). The text contains the theory and algorithms needed for building NLP tools. Topics covered include: mathematical and linguistic foundations; statistical methods; collocation finding; word sense disambiguation; and probalistic parsing. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Detalles bibliogr�ficos

T�tulo: Foundations of Statistical Natural Language Processing (Hardcover)
Editor: MIT Press Ltd, Cambridge, Mass.
Fecha de publicaci�n: 1999
Idioma: Ingl�s
ISBN 10: 0262133601
ISBN 13: 9780262133609
Encuadernaci�n: Hardcover
Edici�n: 1� Edici�n
Estado: new

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Sinopsis

Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.

Cr�ticas

"Statistical natural-language processing is, in my estimation, one ofthe most fast-moving and exciting areas of computer science thesedays. Anyone who wants to learn this field would be well advised toget this book. For that matter, the same goes for anyone who isalready in the field. I know that it is going to be one of the mostwell-thumbed books on my bookshelf." Eugene Charniak , Department of Computer Science, Brown University

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