Deep text : using text analytics to conquer information overload, get real value from social media, and add big(ger) text to big data /

Deep text : using text analytics to conquer information overload, get real value from social media, and add big(ger) text to big data /

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Bibliographic Details
Author / Creator:	Reamy, Tom, author.
Imprint:	Medford, NJ : Information Today, Inc., 2016.
Description:	1 online resource
Language:	English
Subject:	Data mining. Text processing (Computer science) Text files -- Analysis. Big data. Social media. Electronic data processing. Big data. Data mining. Electronic data processing. Social media. Text processing (Computer science)
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11407519

Hidden Bibliographic Details
ISBN:	1573876852 9781573876858 9781573876865 1573876860 9781573875295 1573875295
Notes:	Includes bibliographical references and index. Text in English. Print version record.
Summary:	"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"--EBSCOHost
Other form:	Print version: 9781573875295 1573875295

Table of Contents:

Introduction: Text analytics and text mining; What is text analytics?; Is deep learning the answer?; Text analytics, deep text, and context; Who am I?; Plan of the book
Text analytics basics
Getting started in text analytics
Text analytics development
Text analytics applications
Enterprise text analytics as a platform.