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.
Foundations of Statistical Natural Language Processing
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"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
About the Author
Christopher D. Manning is Assistant Professor in the Department of Computer Science at Stanford University. Hinrich Schütze is on the Research Staff at the Xerox Palo Alto Research Center.
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First Sentence
THE AIM of a linguistic science is to be able to characterize and explain the multitude of linguistic observations circling around us, in conversations, writing, and other media. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
THE AIM of a linguistic science is to be able to characterize and explain the multitude of linguistic observations circling around us, in conversations, writing, and other media. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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1 of 1 people found the following review helpful
Format:Hardcover
If you can only own one book about statistical NLP, and the choice is down to this one or Jurafsky and Martin, choose this one. The mathematics is little more rigorous, but by no means daunting, and the exposition is clearer than J&M.
By A Customer
Format:Hardcover
this is an import pre-req to any research/inquiry into this field.
Format:Hardcover
Only buy this book if you want a very technical book about this subject. I bought this book because I was generally interested in this research field... and I never read it. If you are a researcher or a student studying this field, then this might be a good book. Otherwise, there are books that you will probably enjoy more.
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4.7 out of 5 stars
Most recent customer reviews
5.0 out of 5 stars
Self-content and instructive, read the TOC first!
Compared to the slightly overrated Jurafsky and Martin's classic, this book aims less targets but hits them all more precisely, completely and satisfactory for the reader. Read more
Published on May 25 2002 by Peter Alfheim
4.0 out of 5 stars
Perhaps looking somewhere else might help..
I was likely spoiled by some great course notes (courtesy of Jan Hajic). So when I found Manning and Schutze to be of little help, it was likely because it was too much of an... Read more
Published on Dec 27 2001 by Tahir Butt
5.0 out of 5 stars
Which NLP techniques to apply?
If you need a good introductory textbook on NLP, look no further. While doing a project on information extraction of protein-protein interactions from biological free text, I was... Read more
Published on May 11 2001 by Kah Tong, Seow
5.0 out of 5 stars
Complete & Self-Contained
In 1957, J. R. Firth coined the phrase "You shall know a word by the company it keeps", unfortunately it's taken almost four decades for us to create the technology and... Read more
Published on Nov 22 2000 by Chris McKinstry
5.0 out of 5 stars
Fantastic return on investment
There are lots of books (and even more junk email) with titles like "Get Rich Quick". On the surface, this book is the exact opposite: a scholarly, scientific text... Read more
Published on Sep 12 2000 by Peter Norvig
5.0 out of 5 stars
Makes a great textbook...
My professor chose this book for a undergraduate course in Statistical Natural Language Processing and as a student I found it to be a great learning tool. Read more
Published on April 8 2000
5.0 out of 5 stars
An absolute MUST for anyone interested in NLP.
This is the best book I've ever read on computational linguistics. It should be ideal for both linguists who want to learn about statistical language processing and those... Read more
Published on May 26 1999 by Bob Carpenter (carp@research.bell-labs.com)
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