Free Downloads Text Mining And Analysis: Practical Methods, Examples, And Case Studies Using SAS
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.
Perfect Paperback: 340 pages
Publisher: SAS Institute (October 25, 2013)
Language: English
ISBN-10: 161290551X
ISBN-13: 978-1612905518
Product Dimensions: 8.2 x 0.8 x 11 inches
Shipping Weight: 2.1 pounds (View shipping rates and policies)
Average Customer Review: 4.8 out of 5 stars See all reviews (5 customer reviews)
Best Sellers Rank: #431,260 in Books (See Top 100 in Books) #285 in Books > Computers & Technology > Software > Mathematical & Statistical #1087 in Books > Textbooks > Science & Mathematics > Mathematics > Statistics #1645 in Books > Science & Math > Mathematics > Applied > Probability & Statistics
Solid book - lots of walk-through on "how to use" and could have benefitted from results. What was the pay-off? What does one get for all that effort in terms of actionable decisions, next steps, etc.
This book gives a great introduction to text mining, even for those who are not using SAS. I think it's helpful to have a discussion of the high-level details of the implementation of text mining methods along with descriptions of the methods themselves. The book does a nice job highlighting the important tasks along the way from text collection to the various forms of possible analysis using the document-term matrix.
I have known professor Chakraborty for various years now and have attended various of his talks which have been very inspiring to me. One of the things which always strikes me about him, is how he manages to bridge the gap between analytics as a technical discipline, and analytics as a practitioner-focused, value adding business activity.Throughout the many master projects which he supervised in collaboration with various Fortune 500 companies, prof. Chakraborty managed to acquire a unique experience and skill set. The book is the fruitful result of this. It reports extensively on the many case studies prof. Chakraborty conducted in the past few years.What is unique about this book, is that it gives plenty of practical insights, examples, tips and tricks of how to use text mining and analysis in a practical setting. Prior SAS experience is useful but not strictly necessary to read the book. It is very easy to read with a good flow and structure. Whether you are business practitioner, (MBA) student, PhD researcher, or professor I would highly recommend the book to understand the full potential of text analytics.Bart Baesens, Professor of Big Data and Analytics, KU Leuven (Belgium), www.dataminingapps.com
A complex problems are presented clearly and neatly.
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