did-you-know? rent-now

Rent More, Save More! Use code: ECRENTAL

did-you-know? rent-now

Rent More, Save More! Use code: ECRENTAL

5% off 1 book, 7% off 2 books, 10% off 3+ books

9781119487128

Text as Data Computational Methods of Understanding Written Expression Using SAS

by ;
  • ISBN13:

    9781119487128

  • ISBN10:

    1119487129

  • Edition: 1st
  • Format: Hardcover
  • Copyright: 2021-10-05
  • Publisher: Wiley

Note: Supplemental materials are not guaranteed with Rental or Used book purchases.

Purchase Benefits

List Price: $64.00 Save up to $16.00
  • Rent Book $48.00
    Add to Cart Free Shipping Icon Free Shipping

    TERM
    PRICE
    DUE
    USUALLY SHIPS IN 3-4 BUSINESS DAYS
    *This item is part of an exclusive publisher rental program and requires an additional convenience fee. This fee will be reflected in the shopping cart.

How To: Textbook Rental

Looking to rent a book? Rent Text as Data Computational Methods of Understanding Written Expression Using SAS [ISBN: 9781119487128] for the semester, quarter, and short term or search our site for other textbooks by DeVille, Barry; Singh Bawa, Gurpreet. Renting a textbook can save you up to 90% from the cost of buying.

Summary

Text As Data: Combining qualitative and quantitative algorithms within the SAS system for accurate, effective and understandable text analytics

The need for powerful, accurate and increasingly automatic text analysis software in modern information technology has dramatically increased. Fields as diverse as financial management, fraud and cybercrime prevention, Pharmaceutical R&D, social media marketing, customer care, and health services are implementing more comprehensive text-inclusive, analytics strategies. Text as Data: Computational Methods of Understanding Written Expression Using SAS presents an overview of text analytics and the critical role SAS software plays in combining linguistic and quantitative algorithms in the evolution of this dynamic field.

Drawing on over two decades of experience in text analytics, authors Barry deVille and Gurpreet Singh Bawa examine the evolution of text mining and cloud-based solutions, and the development of SAS Visual Text Analytics. By integrating quantitative data and textual analysis with advanced computer learning principles, the authors demonstrate the combined advantages of SAS compared to standard approaches, and show how approaching text as qualitative data within a quantitative analytics framework produces more detailed, accurate, and explanatory results.

  • Understand the role of linguistics, machine learning, and multiple data sources in the text analytics workflow
  • Understand how a range of quantitative algorithms and data representations reflect contextual effects to shape meaning and understanding
  • Access online data and code repositories, videos, tutorials, and case studies
  • Learn how SAS extends quantitative algorithms to produce expanded text analytics capabilities
  • Redefine text in terms of data for more accurate analysis

This book offers a thorough introduction to the framework and dynamics of text analytics—and the underlying principles at work—and provides an in-depth examination of the interplay between qualitative-linguistic and quantitative, data-driven aspects of data analysis. The treatment begins with a discussion on expression parsing and detection and provides insight into the core principles and practices of text parsing, theme, and topic detection. It includes advanced topics such as contextual effects in numeric and textual data manipulation, fine-tuning text meaning and disambiguation. As the first resource to leverage the power of SAS for text analytics, Text as Data is an essential resource for SAS users and data scientists in any industry or academic application. 

Author Biography

Barry DeVille is a Data Scientist and Solutions Architect with 18 years of experience working at SAS. He led the development of the KnowledgeSEEKER decision tree package and has given workshops and tutorials on decision trees for Statistics Canada, the American Marketing Association, the IEEE, and the Direct Marketing Association.

Gurpreet Singh Bawa is the Data Science Senior Manager at Accenture PLC in India. He delivers advanced analytics solutions for global clients in a variety of corporate sectors.

Table of Contents

Preface xi

Acknowledgments xiii

About the Authors xv

Introduction 1

Chapter 1 Text Mining and Text Analytics 3

Chapter 2 Text Analytics Process Overview 15

Chapter 3 Text Data Source Capture 33

Chapter 4 Document Content and Characterization 43

Chapter 5 Textual Abstraction: Latent Structure, Dimension Reduction 73

Chapter 6 Classification and Prediction 103

Chapter 7 Boolean Methods of Classification and Prediction 125

Chapter 8 Speech to Text 139

Appendix A Mood State Identification in Text 157

Appendix B A Design Approach to Characterizing Users Based on Audio Interactions on a Conversational AI Platform 175

Appendix C SAS Patents in Text Analytics 189

Glossary 197

Index 203

Supplemental Materials

What is included with this book?

The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.

Rewards Program