Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS

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9781612905518: Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS
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Big data: It's unstructured, it's coming at you fast, and there's lots of it. In fact, the majority of big data is text-oriented, thanks to the proliferation of online sources such as blogs, emails, and social media.

However, having big data means little if you can't leverage it with analytics. Now you can explore the large volumes of unstructured text data that your organization has collected with Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS.

This hands-on guide to text analytics using SAS provides detailed, step-by-step instructions and explanations on how to mine your text data for valuable insight. Through its comprehensive approach, you'll learn not just how to analyze your data, but how to collect, cleanse, organize, categorize, explore, and interpret it as well. Text Mining and Analysis also features an extensive set of case studies, so you can see examples of how the applications work with real-world data from a variety of industries.

Text analytics enables you to gain insights about your customers' behaviors and sentiments. Leverage your organization's text data, and use those insights for making better business decisions with Text Mining and Analysis.

This book is part of the SAS Press program.

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About the Author:

Dr. Goutam Chakraborty has a B. Tech (Honors) in mechanical engineering from the Indian Institute of Technology, Kharagpur; a PGCGM from the Indian Institute of Management, Calcutta; and an MS in statistics and a PhD in marketing from the University of Iowa. He has held managerial positions with a subsidiary of Union Carbide, USA, and with a subsidiary of British American Tobacco, UK. He is a professor of marketing at Oklahoma State University, where he has taught business analytics, marketing analytics, data mining, advanced data mining, database marketing, new product development, advanced marketing research, web-business strategy, interactive marketing, and product management for more than 20 years. Goutam has presented numerous programs and workshops to executives, educators, and research professionals in the US, Europe, Asia, and the Middle East. He has won many teaching awards, including the SAS Distinguished Professor Award from SAS Institute, and he teaches the popular SAS Business Knowledge Series course, "Text Analytics and Sentiment Mining Using SAS." Goutam's research has been published in many scholarly journals, such as the Journal of Interactive Marketing, Journal of Advertising Research, Journal of Advertising, Journal of Business Research, and Industrial Marketing Management. He coauthored the book Contemporary Database Marketing. In addition, Goutam has served on the editorial review board of the Journal of Business Research and Journal of Academy of Marketing Science. He serves as a member of the SAS Customer Analytics Advisory Board and the JMP Discovery Summit Steering Committee. Goutam has also consulted extensively on issues related to developing digital business strategy, building and managing customer relationships, product development, and management and creation of e-business models with companies such as Aetna, Mercruiser, Thrifty Rent-A-Car, Berendsen Fluid Power, Globe Life Insurance, Vanguard Realtors, Hilti, and Love's Travel Stops. He is the founder of the SAS and OSU Data Mining Certificate program as well as the SAS and OSU Business Analytics Certificate program at Oklahoma State University.

Review:

"Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS is much more than a guide to real-world application of SAS Text Miner. The authors present a case-driven approach to explain the broad field of text analytics, the techniques and mathematics behind the curtain, and the advanced capabilities of the SAS toolset.

"When many people think of text analytics, they immediately think of search technologies. Search is only the beginning of the story in text analytics. Natural language processing, predictive modeling and classification, and sentiment analysis are a few examples of other techniques in text analytics that can drive tremendous business value. The authors provide a cogent, example-rich, and understandable introduction to text analytics, including one of the central techniques for analyzing high-dimensional data: the singular value decomposition.

"I would recommend this book as a foundation to anyone interested in applying text mining to real-world problems; the authors' deft presentation of theory and case-based practical application will arm you with the knowledge you need to derive real insight and value from your textual data." --Mark Pitts, MS, MAcc, Senior Vice President, Analytics, SourceHOV

"Text Mining and Analysis is a must read for anyone working in analyzing textual information. It provides a comprehensive, yet concise overview of text analytics with a focus on the business application." --Prof. Dr. Bart Baesens, Programme Coordinator, Master of Information Management,Department of Decision Sciences and Information Management, Katholieke Universiteit Leuven

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