Taming Text: How to Find, Organize, and Manipulate It

Posted By: nebulae
Taming Text: How to Find, Organize, and Manipulate It

Grant S. Ingersoll, Thomas S. Morton and Andrew L. Farris, "Taming Text: How to Find, Organize, and Manipulate It"
English | ISBN: 193398838X | 2013 | PDF, EPUB | 320 pages | 10 + 10 MB

There is so much text in our lives, we are practically drowning in it. Fortunately, there are innovative tools and techniques for managing unstructured information that can throw the smart developer a much-needed lifeline. You'll find them in this book.

Taming Text is a practical, example-driven guide to working with text in real applications. This book introduces you to useful techniques like full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. You'll explore real use cases as you systematically absorb the foundations upon which they are built. Written in a clear and concise style, this book avoids jargon, explaining the subject in terms you can understand without a background in statistics or natural language processing. Examples are in Java, but the concepts can be applied in any language.

Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.
What's Inside
When to use text-taming techniques
Important open-source libraries like Solr and Mahout
How to build text-processing applications
About the Authors

Grant Ingersoll is an engineer, speaker, and trainer, a Lucene committer, and a cofounder of the Mahout machine-learning project. Thomas Morton is the primary developer of OpenNLP and Maximum Entropy. Drew Farris is a technology consultant, software developer, and contributor to Mahout, Lucene, and Solr.

"Takes the mystery out of very complex processes."—From the Foreword by Liz Liddy, Dean, iSchool, Syracuse University

Table of Contents
Getting started taming text
Foundations of taming text
Fuzzy string matching
Identifying people, places, and things
Clustering text
Classification, categorization, and tagging
Building an example question answering system
Untamed text: exploring the next frontier