Deep Text

by Tom Reamy, Lambe Forword by

Overview

Deep text is an approach to text analytics that adds depth to our ability to utilize a growing mass of unstructured text the world is drowning in. Here, 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. This is an important book 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, Deep Text will supply the insights and examples you'll need to do it effectively.

Product Details

ISBN-13:	9781573876865
Publisher:	Information Today, Inc.
Publication date:	07/19/2016
Sold by:	Barnes & Noble
Format:	eBook
File size:	4 MB

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. For more than a decade, Tom’s primary focus has been on text analytics and helping clients select the best text analytics software as well as doing text analytics development projects that include applications such as call support, voice of the customer, social media analysis, sentiment analysis, enterprise search, and multiple enterprise text analytics–powered applications. Tom’s academic background includes a master’s in the history of ideas, research in artificial intelligence and cognitive science, and a strong background in philosophy, particularly epistemology.