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Text as Data: Computational Methods of Understanding Written Expression Using SA

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Specificaties

Objectstaat
Nieuw: Een nieuw, ongelezen en ongebruikt boek in perfecte staat waarin geen bladzijden ontbreken of ...
ISBN-13
9781119487128
Book Title
Text as Data
ISBN
9781119487128
Publication Name
Text As Data : Computational Methods of Understanding Written Expression Using Sas
Item Length
9in
Publisher
Wiley & Sons, Incorporated, John
Publication Year
2021
Series
Wiley and Sas Business Ser.
Type
Textbook
Format
Hardcover
Language
English
Item Height
1in
Author
Barry Deville, Gurpreet Singh Bawa
Item Width
6.1in
Item Weight
15.2 Oz
Number of Pages
240 Pages

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Product Information

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.

Product Identifiers

Publisher
Wiley & Sons, Incorporated, John
ISBN-10
1119487129
ISBN-13
9781119487128
eBay Product ID (ePID)
26038790600

Product Key Features

Author
Barry Deville, Gurpreet Singh Bawa
Publication Name
Text As Data : Computational Methods of Understanding Written Expression Using Sas
Format
Hardcover
Language
English
Publication Year
2021
Series
Wiley and Sas Business Ser.
Type
Textbook
Number of Pages
240 Pages

Dimensions

Item Length
9in
Item Height
1in
Item Width
6.1in
Item Weight
15.2 Oz

Additional Product Features

Lc Classification Number
Qa76.9.D343d4324
Table of Content
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
Copyright Date
2022
Topic
Programming / General, General, Data Processing, Databases / General
Lccn
2021-033911
Dewey Decimal
006.312
Intended Audience
Scholarly & Professional
Dewey Edition
23
Genre
Computers, Mathematics

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