Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit

Front Cover
"O'Reilly Media, Inc.", Jun 12, 2009 - Computers - 504 pages
5 Reviews

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.

What people are saying - Write a review

User ratings

5 stars
4 stars
3 stars
2 stars
1 star

User Review - Flag as inappropriate


User Review - Flag as inappropriate

If you are looking for a book about doing Python programming with NLTK (the natural language toolkit, then this is the book for you! Sure, you could code these algorithms by yourself, but that would be expending energy on the methods and not on obtaining good results. That's where the toolkit comes in.
This book attempts to show you how to install NLTK and Python, but I found that I needed to check the web for more guidance, since there are too many versions of Python and also I'm working from behind a proxy, adding to my difficulties.
Sure, it might be a little more difficult to install Python and NLTK than the book suggests. But once you get your NLTK set up, this book is very clear and lucid. It leads you, step by step, into the different NLP (natural language processing) operations that can be performed with NLTK. I definitely recommend this book to others interested in NLP.


Chapter 1 Language Processing and Python
Chapter 2 Accessing Text Corpora and Lexical Resources
Chapter 3 Processing Raw Text
Chapter 4 Writing Structured Programs
Chapter 5 Categorizing and Tagging Words
Chapter 6 Learning to Classify Text
Chapter 7 Extracting Information from Text
Chapter 8 Analyzing Sentence Structure
Chapter 9 Building FeatureBased Grammars
Chapter 10 Analyzing the Meaning of Sentences
Chapter 11 Managing Linguistic Data
The Language Challenge
NLTK Index
General Index

Other editions - View all

Common terms and phrases

Bibliographic information