Summary
Taming Text, winner of the 2013 Jolt Awards for Productivity, is a hands-on, example-driven guide to working with unstructured text in the context of real-world applications. This book explores how to automatically organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. The book guides you through examples illustrating each of these topics, as well as the foundations upon which they are built.
About this Book
There is so much text in our lives, we are practically drowningin it. Fortunately, there are innovative tools and techniquesfor managing unstructured information that can throw thesmart developer a much-needed lifeline. You'll find them in thisbook.
Taming Text is a practical, example-driven guide to working withtext 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 thefoundations upon which they are built.
Written in a clear and concise style, this book avoids jargon, explainingthe subject in terms you can understand without a backgroundin statistics or natural language processing. Examples arein Java, but the concepts can be applied in any language.
Written for Java developers, the book requires no prior knowledge of GWT.
What's Inside
• When to use text-taming techniques
• Important open-source libraries like Solr and Mahout
• How to build text-processing applicationsAbout the Authors
Grant Ingersoll is an engineer, speaker, and trainer, a Lucenecommitter, 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.
Table of Contents
• Getting started taming text
• Foundations of taming text
• Searching
• 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
