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Foundations of Statistical Natural Language…
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Foundations of Statistical Natural Language Processing

by Christopher D. Manning, Hinrich Schütze

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Along with Speech and Natural Language Processing by Jurafsky and Martin, this is the standard book on using probabilistic methods to analyze natural language. It has clear discussions of such core areas as N-gram language modeling, parsing, part of speech tagging, and information retrieval. The exceptionally lucid chapter on Hidden Markov Models is worth the price of the book alone. This is the best introductory textbook for newcomers and a useful reference for everyone else. Essential. ( )
  billmcn | May 16, 2007 |
Although the required text for the class in statistical natural language processing, this was not as clear, particularly regarding algorithms, as "Speech and Language Processing" by Jurafsky and Martin. ( )
  billlund | Dec 26, 2006 |
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Author nameRoleType of authorWork?Status
Christopher D. Manningprimary authorall editionsconfirmed
Schütze, Hinrichmain authorall editionsconfirmed
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Amazon.com Product Description (ISBN 0262133601, 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.

(retrieved from Amazon Mon, 30 Sep 2013 13:18:52 -0400)

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