Text as data : computational methods of understanding written expression using SAS / Barry deVille, Gurpreet Singh Bawa.

Format:

Book

Author/Creator:

De Ville, Barry, author.

Bawa, Gurpreet Singh, 1983- author.

Series:

Wiley and SAS business series.

Wiley and SAS business series

Language:

English

Subjects (All):

Text data mining.

Computational intelligence.

SAS (Computer program language).

Physical Description:

1 online resource (235 pages)

Place of Publication:

Hoboken, NJ : John Wiley & Sons, Inc., [2022]

Summary:

This book offers a thorough introduction to the framework and dynamics of text analyticsand the underlying principles at workand provides an in-depth examination of the interplay between qualitative-linguistic and quantitative, data-driven aspects of data analysis. -- Edited summary from book

Contents:

Cover

Title Page

Copyright Page

Contents

Preface

Acknowledgments

About the Authors

Introduction

Chapter 1 Text Mining and Text Analytics

Background and Terminology

Text Analytics: What Is It?

Brief History of Text

Writing Systems of the World

Meaning and Ambiguity

Notes

Chapter 2 Text Analytics Process Overview

Text Analytics Processing

Process Building Blocks

Preparation

Utilization

Process Description

Text Mining Data Sources

Capture

Linguistic Processing

Parsing and Parse Products

Internal Representation and Text Products

Representation

Chapter 3 Text Data Source Capture

Text Mining Data Source Assembly

Use Case: Accessing Text from SAS Conference Proceedings

Text Data Capture Process

Consuming Linguistics Text Products

Chapter 4 Document Content and Characterization

Authorship Analytics: Early Text Indicators and Measures

Function Words as Indicators

Beyond Function Words

Words and Word Forms as Psychological Artifacts

A Case Study in Gender Detection

Data Product Example

Analysis Results

Summarization and Discourse Analysis

Elementary Operations as Building Blocks to Results

Fact Extraction

Sentiment Extraction

Conditional Inference

Deployment

Summarization

Conclusion

Chapter 5 Textual Abstraction: Latent Structure, Dimension Reduction

Latent Structure and Dimensional Reduction

Singular Value Decomposition as Dimension Reduction

Latent Semantic Analysis

Clustering Approach to Document Classification

SVD Approach to Document Indexing

Rough Meaning - Approximation for Singular Value Dimensions

Semantic Indexing: Assigning Category Based on Singular Value Dimensional Scores

Identifying Topics Using Latent Structure.

Latent Structure: Tracking Topic Term Variability Across Semantic Fields

Chapter 6 Classification and Prediction

Use Case Scenario

Composite Document Construction

Model Development

Ensemble or Multiagent Models

Identifying Drivers of Textual Consumer Feedback Using Distance-Based Clustering and Matrix Factorization

Use Case Scenario: Retailer Reliability Ecommerce

Discussion

Chapter 7 Boolean Methods of Classification and Prediction

Rule-Based Text Classification and Prediction

Method Description

Characteristics of Boolean Rule Methods

Example of Boolean Rules Applied to Text Mining Vaccine Data

An Example Analysis

Summary

Chapter 8 Speech to Text

Processing Audio Feedback

Business Problem

Process Components

Further Analysis: Sentiment and Latent Topics

Appendix A Mood State Identification in Text

Origins of Mood State Identification

An Approach to Mood State Developed at SAS

Background and Discussion

An Example Mood State Process Flow

Appendix B A Design Approach to Characterizing Users Based on AudioInteractions on a Conversational AI Platform

Audio-Based User Interaction Inference

Recommendation Perspective vs. Conventional

Sole Dependency on Text-Based Bots

Implementation Scenario: Voice-Based Conversational AI Platform

Component Process Flow

Constructed Interaction

Note

Appendix C SAS Patents in Text Analytics

Glossary

Index

EULA.

Notes:

Description based on print version record.

ISBN:

9781119487142

1119487145

9781119487159

1119487153

OCLC:

1276854343