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Natural Language Processing with Python [Paperback]

by Steven Bird, Ewan Klein, Edward Loper
4.0 out of 5 stars  See all reviews (26 customer reviews)

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Book Description

July 10, 2009 0596516495 978-0596516499 1

This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.

Packed with examples and exercises, Natural Language Processing with Python will help you:

  • Extract information from unstructured text, either to guess the topic or identify "named entities"
  • Analyze linguistic structure in text, including parsing and semantic analysis
  • Access popular linguistic databases, including WordNet and treebanks
  • Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence


This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

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Editorial Reviews

Book Description

Analyzing Text with the Natural Language Toolkit

About the Author

Steven Bird is Associate Professor in the Department of Computer Science and Software Engineering at the University of Melbourne, and Senior Research Associate in the Linguistic Data Consortium at the University of Pennsylvania. He completed a PhD on computational phonology at the University of Edinburgh in 1990, supervised by Ewan Klein. He later moved to Cameroon to conduct linguistic fieldwork on the Grassfields Bantu languages under the auspices of the Summer Institute of Linguistics. More recently, he spent several years as Associate Director of the Linguistic Data Consortium where he led an R&D team to create models and tools for large databases of annotated text. At Melbourne University, he established a language technology research group and has taught at all levels of the undergraduate computer science curriculum. In 2009, Steven is President of the Association for Computational Linguistics.

Ewan Klein is Professor of Language Technology in the School of Informatics at the University of Edinburgh. He completed a PhD on formal semantics at the University of Cambridge in 1978. After some years working at the Universities of Sussex and Newcastle upon Tyne, Ewan took up a teaching position at Edinburgh. He was involved in the establishment of Edinburgh's Language Technology Group in 1993, and has been closely associated with it ever since. From 2000-2002, he took leave from the University to act as Research Manager for the Edinburgh-based Natural Language Research Group of Edify Corporation, Santa Clara, and was responsible for spoken dialogue processing. Ewan is a past President of the European Chapter of the Association for Computational Linguistics and was a founding member and Coordinator of the European Network of Excellence in Human Language Technologies (ELSNET).

Edward Loper has recently completed a PhD on machine learning for natural language processing at the the University of Pennsylvania. Edward was a student in Steven's graduate course on computational linguistics in the fall of 2000, and went on to be a TA and share in the development of NLTK. In addition to NLTK, he has helped develop two packages for documenting and testing Python software, epydoc, and doctest.


Product Details

  • Paperback: 504 pages
  • Publisher: O'Reilly Media; 1 edition (July 10, 2009)
  • Language: English
  • ISBN-10: 0596516495
  • ISBN-13: 978-0596516499
  • Product Dimensions: 9.2 x 6.9 x 1.2 inches
  • Shipping Weight: 1.5 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (26 customer reviews)
  • Amazon Best Sellers Rank: #125,243 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews
104 of 109 people found the following review helpful
4.0 out of 5 stars Heavy on code, somewhat light on theory July 19, 2009
Format:Paperback
This book really delivers when it comes to code. It starts with simple tasks using the Python NLTK (Natural Language Toolkit) and builds up from there, teaching you a little bit of Python, a little bit of NLP theory, and delivering much in the way of useful applications. The author takes the time to explain the code and what is going on behind the scenes. He starts with extracting explicit words from documents and builds on that until at the end of the book you are analyzing sentence structure and building feature-based grammars.

This is not, however, an introduction to either the mathematics or information theory of natural language processing. It is not even a tutorial on Python. The book's sole purpose is to help you solve real problems using a common language without necessarily understanding the theory or the language you are using. If you really want to understand Python I suggest Learning Python. It's not as interestng as this book, but it gets the job done. To understand the theory behind natural language processing and also see how algorithms are coded up I suggest An Introduction to Language Processing with Perl and Prolog: An Outline of Theories, Implementation, and Application with Special Consideration of English, French, and German (Cognitive Technologies).

As for this book, I think it makes a great supplement to the other books I mention and also as a recipe book of solutions to real-world problems. I really don't think it is a gentle introduction to
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42 of 42 people found the following review helpful
4.0 out of 5 stars Good book, great library September 21, 2009
Format:Paperback|Verified Purchase
Buy this book only if you:
1. Know the basics of natural language processing (NLP) or linguistics;
2. Know the Python programming language or you're willing to learn it;
3. Are using the NLTK library or plan to do so.

NLTK is a Python library that offers many standard NLP tools (tokenizers, POS taggers, parsers, chunkers and others). It comes with samples of several dozens of text corpora typically used in NLP applications, as well as with interfaces to dictionary-like resources such as WordNet and VerbNet. No FrameNet, though. NLTK is well documented, so you might not need this book initially. However, it definitely helps to have it on your desk if you are serious about using NLTK.

The first chapters are a bit messy, as they attempt to introduce all three themes (NLP, NLTK and Python) together. Beginners may have some difficulty sorting things out. By the time you reach the WordNet section, you either got lost in the forest, realize that you would never understand this topic without the book, or both. However, if you are a bit patient and try out all simple code examples, you'll make it eventually. In my opinion, NLTK remains the simplest, most elegant and well rounded library of its kind.
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15 of 15 people found the following review helpful
Format:Paperback
There are three kinds of people who might think this book could be useful:

1. Natural language processing (NLP) researchers and students who want a learn a solid programming tool to help them with their work.
2. Python programmers who want to find out more about NLP.
3. Newbies in both Python and NLP who just think the topic sounds cool and those whales on the cover are kinda cute.

In my opinion, the only kind that will find this book suitable and useful is (1). If you're familiar with Python and know no NLP it won't help you much, because it doesn't really teach NLP. It shows a few domains of this vast field, with nice code examples and all, but you should probably start with some introductory textbook on the subject or a course. You won't really learn NLP here.

The book's focus is mostly on the NLTK library written in Python by the authors. This library implements many NLP algorithms and comes with lots of data for testing and training. Almost no algorithms are implemented in the book - some are explained, and the code always imports the required modules from NLTK and shows their usage. The Python code is well-written and clean.

To conclude, if you're a NLP researcher or student, this is a very good book to read. Especially if you plan to start working with NLTK (which seems like a mature and powerful tool) - this book will serve as a great introduction. If you have other interests, this is probably not the right book.
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18 of 20 people found the following review helpful
5.0 out of 5 stars Excellent intro to NLP July 17, 2009
Format:Paperback
Excellent introduction to the field of Natural Language Processing. I've been using the Natural Language Toolkit, the Python library explained in this book, for about two years and have seen it continually improve and become more robust. I eagerly awaited this text, which I first learned about over a year ago, and I must say the wait was worth it. Although most useful for those with a background in computer science or linguistics, it's a fairly gentle introduction to the field, so anyone with interest in the subject should find it useful and easy to understand. Stephen, Ewan, and Edward have done an excellent job of explaining language technologies and associated algorithmic functions for analyzing text.
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Most Recent Customer Reviews
1.0 out of 5 stars It's a collection of NLTK docs available on the web!
This book is a collection of the NLTK documentation available on the web. Some of the pages have been copied word by word. Read more
Published 29 days ago by S. Kumar
4.0 out of 5 stars A little out of date already but still good
This is a pretty good book for getting someone started in NLP and Python, I think. My only problem was that some of the code is already rather out of date. Read more
Published 1 month ago by D. Brittany Kidd
2.0 out of 5 stars not a good book
i would rather to have two books instead of one. one for java, the other for NLP. it is quite shallow especially if you are a grad student.
Published 4 months ago by Yifan Peng
4.0 out of 5 stars A Good Introduction to Natural Language Processing with Python.
This is the classic Natural Language with Python book. It's a good introduction to Natural Language Processing with Python. The book lacks depth in places.
Published 5 months ago by Computers Dave
5.0 out of 5 stars Really great book
Informative, clear and very interesting. great for self study. I would definitely recommend this book to anybody interested in NLP and text analysis
Published 6 months ago by a
4.0 out of 5 stars Very interesting
Because it has very interesting examples that help to understand natural language processing, especially with the libraries that help a lot and avoids writing unnecessary code. Read more
Published 8 months ago by Manuel E Sucunuta
5.0 out of 5 stars Outstanding
Excellent coverage of python for the newbie. Good coverage of Natural Language processing for folks who are new to the subject area.
Published 10 months ago by Steven F. Lott
5.0 out of 5 stars Super intro to NLP
I am interested in NLP from a medical standpoint. This book is simultaneously a great intro to NLP and to Python-- although an experienced programmer I have not used Python... Read more
Published 10 months ago by Amazon Customer
3.0 out of 5 stars An OK book but not necessarily needed
First of all, the book does not consist with the up-to-date NLTK version. If you download a new NLTK version but follow this book, you still have to look up the online API. Read more
Published 12 months ago by Marlin
5.0 out of 5 stars Great guide to NLTK
NLTK was originally designed for teaching NLP, but because NLTK is so comprehensive, it is also quite vast, and you will need a guide to get you started on using it effectively. Read more
Published 16 months ago by Sujit Pal
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