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

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