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Deep Text by Tom Reamy

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

Pub Date: July 26th, 2016
ISBN: 978-1-57387-529-5
Publisher: Information Today Inc

A treasure trove of technical detail, likely to become a definitive source on text analytics.

This debut book by Reamy, the founder of the KAPS Group consultancy, is a highly targeted, in-depth study of an emerging area of technology—the process of analyzing large volumes of text via a variety of technical means in order to gain deeper understanding and insight into its content. In Part 1, the author defines the specific components of text analytics and describes its basics. He also eloquently discusses its value, asserting that it can save money and enhance productivity by, for example, increasing the accuracy of employee searches for specific documents so that they don’t need to be re-created. Reamy then lays out a comprehensive plan for how to implement text analytics that includes establishing a team, evaluating and implementing software, and developing specific applications. Part 2 then covers all aspects of “getting started” while providing a brief history of the technology, and Part 3 explores the development of text analytics in enterprises and social media, supplemented by case studies that demonstrate best practices. Part 4 describes search-based applications, which he calls “InfoApps,” and Part 5 looks into using text analytics as an enterprise platform. The author’s excellent concluding chapter offers a tidy summary of the entire book as well as an essay on the future with forays into cognitive computing, which “largely consists of machine learning and neural networks,” and “deep text semantic infrastructure,” which essentially tracks and comprehends content throughout an entire enterprise. The real lasting value of text analytics, writes Reamy, will be as “a means of incorporating the whole dimension of semantics and meaning in new, richer, deeper ways that accomplish the ultimate goal—making people smarter.” The book’s copious notes, appendices, and bibliography enrich the text with its lists of text-analytics companies and software and other valuable resources. One of the main strengths of this book, though, is that even when its content is highly technical, it’s so well-organized and tightly written that it’s quite enjoyable to read.

A remarkably authoritative, deep dive into a field that will be brand-new to many and eye-opening for all.