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Foundations of Statistical Natural Language Processing

4.17  ·  Rating details ·  236 ratings  ·  16 reviews
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 found ...more
Hardcover, 679 pages
Published May 28th 1999 by MIT Press
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Michael Shaw
Dec 06, 2011 rated it it was amazing
A must read for anyone looking to get into NLP. Teaches from first principles, including briefly touching on information theory/entropy. I felt it was well grounded, and proceded at a good pace. No prior knowledge is required.

I picked this up at the same time as "Speech and Language Processing" (Jurafsky & Martin) and while Foundations is a much narrower book (making up with depth), I think it's for the better, as I found SLP far too broad and thin.
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Ushan
Dec 28, 2010 rated it liked it
As the great American anthropologist-linguist Edward Sapir put it, all grammars leak. Some sentences are obviously grammatical, some are obviously ungrammatical, but there are gray areas; native speakers of English disagree on whether sentences such as "Who did Jo think said John saw him?" and "The boys read Mary's stories about each other" are grammatical. A way of resolving this difficulty is to look at a large corpus of texts; sentence structures that occur there often are grammatical, senten ...more
Emmi
Dec 14, 2017 rated it liked it
Shelves: education
Explanation on basic idea on NLP is very good, but only this book is not enough to get entire idea on NLP. Better to read "Speech and Language Processing" as well (By Dan Jurafsky, James H. Martin ).
Ane
Feb 22, 2019 rated it really liked it
Very good introductory book to NLP, a little oudated.
Daniel Smith
Feb 03, 2018 rated it liked it
A bit dated now, but still a solid introduction to NLP.
Terran M
May 19, 2018 rated it really liked it
A classic on natural language processing. If you know nothing about natural language processing, or have a piecemeal understanding, this book will give you an overview of the field in a rigorous and yet comprehensible way.

Note that this book was written in 1999, so it far predates the current practice to use recursive neural networks for natural language. This book will give you exactly what it says in the title, Foundations, not “modern best practices.”

You may also be interested in Introduction
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Douglas Summers-Stay
May 04, 2015 rated it really liked it
Shelves: non-fiction
This 1999 book does a good job of explaining the different areas of statistical NLP. It was easy to read and very clear, even the formula-heavy sections. The sections on collocations (multi-word phrases) and verb subcategorization were largely new to me.
The problems that natural-language research has faced are similar to the ones computer vision faces, but easier. What that means is that the researchers have made a lot more progress in the higher-level organization of concepts instead of getting
...more
Bill
May 16, 2007 rated it it was amazing
Recommends it for: anyone working in computational linguistics
Shelves: nlp, non-fiction
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 a good starting textbook for newcomers and a useful reference for everyone else. Essential.
David
This and Speech and Language Processing by Jurafsky and Martin are the two big introductory texts in natural language processing. I prefer the Jurafsky book; it goes into more detail, has more examples, and is written more for use as a class text. The Manning and Schutze book is much more mathematically oriented and goes into more detail on algorithms, so if you're focusing on the statistical aspect more than the language aspect, refer to this book. Ideally, you probably want both.
Rachid El guerrab
May 10, 2012 rated it liked it
Needs more walk-through integrated examples, not just simple illustrations for specific paragraphs.

It could also benefit from a discussion of NLP software and possible architectures for the domain.
Brian
Apr 19, 2011 is currently reading it
Currently it's a bit tough for me to read because I haven't formally studied logic or statistics... but a well written book
Vít Baisa
Jan 01, 2015 rated it really liked it
Sometimes it felt a bit out-dated but the explanations of various algorithms and principles was very good and understanable.
Chris Irwin Davis
Apr 08, 2011 rated it it was amazing
Shelves: ai
This book is the starting point for any serious study of the discipline.
Gabriela Crippa
This review has been hidden because it contains spoilers. To view it, click here.
Shubhajoy Das
Apr 13, 2013 rated it really liked it
this was a good book loved the exercisesvery few nlp books have such good exercises
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Professor of Linguistics and Computer Science, Natural Language Processing Group, Stanford University

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