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Python 3 Text Processing with NLTK 3 Cookbook

You're reading from Python 3 Text Processing with NLTK 3 Cookbook

Product type Paperback

Published in Aug 2014

Publisher

ISBN-13 9781782167853

Length 304 pages

Edition 2nd Edition

Languages

Python

Tools

NLTK

Concepts

Data Processing

Author (1):

Jacob Perkins

View More author details

Table of Contents (12) Chapters

Preface

1. Tokenizing Text and WordNet Basics FREE CHAPTER

2. Replacing and Correcting Words

3. Creating Custom Corpora

4. Part-of-speech Tagging

5. Extracting Chunks

6. Transforming Chunks and Trees

7. Text Classification

8. Distributed Processing and Handling Large Datasets

9. Parsing Specific Data Types

A. Penn Treebank Part-of-speech Tags

Index

Chapter 5. Extracting Chunks

In this chapter, we will cover the following recipes:

Chunking and chinking with regular expressions
Merging and splitting chunks with regular expressions
Expanding and removing chunks with regular expressions
Partial parsing with regular expressions
Training a tagger-based chunker
Classification-based chunking
Extracting named entities
Extracting proper noun chunks
Extracting location chunks
Training a named entity chunker
Training a chunker with NLTK-Trainer

The rest of the chapter is locked

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Authors (1)

Jacob Perkins

Jacob Perkins

Jacob Perkins is the cofounder and CTO of Weotta, a local search company. Weotta uses NLP and machine learning to create powerful and easy-to-use natural language search for what to do and where to go. He is the author of Python Text Processing with NLTK 2.0 Cookbook, Packt Publishing, and has contributed a chapter to the Bad Data Handbook, O'Reilly Media. He writes about NLTK, Python, and other technology topics at http://streamhacker.com. To demonstrate the capabilities of NLTK and natural language processing, he developed http://text-processing.com, which provides simple demos and NLP APIs for commercial use. He has contributed to various open source projects, including NLTK, and created NLTK-Trainer to simplify the process of training NLTK models. For more information, visit https://github.com/japerk/nltk-trainer.

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