Foundations of Statistical Natural Language Processing

by Christopher D. Manning, Hinrich Schütze

Description

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 show more implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications. show less

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Member Recommendations

Speech and language processing : an introduction to natural language processing, computational linguistics, and speech recognition by Daniel Jurafsky

billmcn The other canonical natural language processing textbook

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2 reviews

billmcn 183 reviews

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.

May 16, 2007

billlund 85 reviews

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.

Dec 26, 2006

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