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

Chakraborty, Goutam|Pagolu, Murali|Garla, Satish

ISBN 10: 161290551X / ISBN 13: 9781612905518

Editore: SAS Institute, 2013

Riguardo questo articolo

KlappentextrnrnBig 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. n .

Codice articolo 464697653

Dati bibliografici

• Titolo: Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS
• Editore: SAS Institute
• Data di pubblicazione: 2013
• Lingua: Inglese
• ISBN 10: 161290551X
• ISBN 13: 9781612905518
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

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.

L'autore

Dr. Goutam Chakraborty 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.

Murali Pagolu is a Business Analytics Consultant at SAS. He has rich experience in implementing analytical solutions involving text analytics, predictive modeling, customer segmentation, database marketing, and various data mining techniques for customer relationship management applications. He currently holds six SAS certification credentials.

Satish Garla is an Analytical Consultant in Risk Practice at SAS. He has extensive experience in risk modeling for healthcare, predictive modeling, text analytics, and SAS programming. He has a distinguished background in analytics, databases, and business administration.