One of the most thorough walk troughs of text analytics ever provided.” —Jeff Catlin, CEO, Lexalytics
Medford, New Jersey (PRWEB) August 02, 2016
Information Today, Inc. (ITI) announced the publication of Deep Text: Using Text Analytics to Conquer Information Overload, Get Real Value from Social Media, and Add Big(ger) Text to Big Data by Tom Reamy.
Deep text is an approach to text analytics that adds depth and intelligence to our ability to utilize a growing mass of unstructured text the world is drowning in. Author Tom Reamy explains what deep text is and surveys its many uses and benefits. He describes applications and development best practices, discusses business issues including ROI, provides how-to advice and instruction, and offers guidance on selecting software and building a text analytics capability within an organization.
Deep Text is for anyone who needs to be on the text analytics cutting edge, from developers and information professionals who create, manage, and curate text-based and Big Data projects to entrepreneurs and business managers looking to cut costs and create new revenue streams. Whether you want to harness a flood of social media content or turn a mountain of business information into an organized and useful asset, Reamy supplies insights and examples for analyzing text effectively.
“Text analytics, in its broadest sense, is the major tool for dealing with unstructured text other than the human brain—and there are only a handful of degree programs that cover unstructured text in any depth and they focus mainly on text mining as part of a computer science degree,” states Reamy, in the book’s Introduction. “Because of the complexity of text, text analytics will probably never be as easy to learn as database design and programming. But we can build a better foundation for text analytics to improve not only how we train people in text analytics, but how we understand the business value of text analytics as a whole.”
“This book is written with the practitioner in mind and is full of practical examples and wisdom born of deep experience,” says Patrick Lambe, in the book’s Foreword. “In the process, Reamy takes the field of text analytics from a fragmentary clutch of diverse techniques, with very little methodological consistency, toward what he calls a ‘deep-text’ approach—a framework that integrates well-established knowledge organization methodologies with a portfolio or toolkit approach to the use of methods and techniques, and that is focused on getting repeatable value from a text analytics infrastructure, as distinct from the ad hoc project driven approaches that are so typical today.”
Additional features include the foreword by Patrick Lambe, an introduction by the author, a bibliography, several tables and figures, and an index.
About the Author
Tom Reamy is currently the chief knowledge architect and founder of the KAPS Group, a group of knowledge architecture, text analytics, and taxonomy consultants, and has 20 years of experience in information projects of various kinds. He has published a number of articles in a variety of journals and is a frequent speaker at knowledge management, taxonomy, and text analytics conferences. He has served as the program chair for Text Analytics World since 2013. When not writing or developing text analytics projects, he can usually be found at the bottom of the ocean in Carmel, photographing strange critters.
Deep Text: Using Text Analytics to Conquer Information Overload, Get Real Value from Social Media, and Add Big(ger) Text to Big Data (464 pp/softcover/$59.50/ISBN 978-1-57387-529-5) is published by Information Today, Inc. (ITI) and is available wherever quality books and ebooks are sold. For more information, call (800) 300-9868; fax (609) 654-4309; email custserv(at)infotoday(dot)com, or visit the ITI website at infotoday.com.