Functional Applications of Text Analytics Systems / Steven Simske and Marie Vans.

Format:

Book

Author/Creator:

Simske, Steven, author.

Vans, Marie, author.

Series:

River Publishers Series in Document Engineering

Language:

English

Subjects (All):

Text data mining.

Physical Description:

1 online resource (292 pages)

Edition:

First edition.

Place of Publication:

Gistrup, Denmark : River Publishers, [2021]

Summary:

Text analytics can provide a wide breadth ofvaluable information, including summarization, clustering, classification, andcategorization to enable better functional interaction with the text. Thisincludes improved search, translation, optimization, and learning. In this textadvanced analytical approaches used to enable improved utility of the textdocuments are described and explained.

Contents:

Cover

Half Title

Series Page

Title Page

Copyright Page

Table of Contents

Preface

Acknowledgement

List of Figures

List of Tables

List of Abbreviations

1: Linguistics and NLP

1.1 Introduction

1.2 General Considerations

1.3 Machine Learning Aspects

1.3.1 Machine Learning Features

1.3.2 Other Machine Learning Approaches

1.4 Design/System Considerations

1.4.1 Sensitivity Analysis

1.4.2 Iterative Tradeoff in Approach

1.4.3 Competition - Cooperation Algorithms

1.4.4 Top-Down and Bottom-Up Designs

1.4.5 Agent-Based Models and Other Simulations

1.5 Applications/Examples

1.6 Test and Configuration

1.7 Summary

2: Summarization

2.1 Introduction

2.2 General Considerations

2.2.1 Summarization Approaches - An Overview

2.2.2 Weighting Factors in Extractive Summarization

2.2.3 Other Considerations in Extractive Summarization

2.2.4 Meta-Algorithmics and Extractive Summarization

2.3 Machine Learning Aspects

2.4 Design/System Considerations

2.5 Applications/Examples

2.6 Test and Configuration

2.7 Summary

3: Clustering, Classification, and Categorization

3.1 Introduction

3.1.1 Clustering

3.1.2 Regularization - An Introduction

3.1.3 Regularization and Clustering

3.2 General Considerations

3.3 Machine Learning Aspects

3.3.1 Machine Learning and Clustering

3.3.2 Machine Learning and Classification

3.3.3 Machine Learning and Categorization

3.4 Design/System Considerations

3.5 Applications/Examples

3.5.1 Query-Synonym Expansion

3.5.2 ANOVA, Cross-Correlation, and Image Classification

3.6 Test and Configuration

3.7 Summary

4: Translation

4.1 Introduction

4.2 General Considerations

4.2.1 Review of Relevant Prior Research

4.2.2 Summarization as a Means to Functionally Grade the Accuracy of Translation.

4.3 Machine Learning Aspects

4.3.1 Summarization and Translation

4.3.2 Document Reading Order

4.3.3 Other Machine Learning Considerations

4.4 Design/System Considerations

4.5 Applications/Examples

4.6 Test and Configuration

4.7 Summary

5: Optimization

5.1 Introduction

5.2 General Considerations

5.3 Machine Learning Aspects

5.4 Design/System Considerations

5.5 Applications/Examples

5.5.1 Document Clustering

5.5.2 Document Classification

5.5.3 Web Mining

5.5.4 Information and Content Extraction

5.5.5 Natural Language Processing

5.5.6 Sentiment Analysis

5.5.7 Native vs. Non-Native Speakers

5.5.8 Virtual Reality and Augmented Reality

5.6 Test and Configuration

5.7 Summary

6: Learning

6.1 Introduction

6.1.1 Reading Order

6.1.2 Repurposing of Text

6.1.3 Philosophies of Learning

6.2 General Considerations

6.2.1 Metadata

6.2.2 Pathways of Learning

6.3 Machine Learning Aspects

6.3.1 Learning About Machine Learning

6.3.2 Machine Learning Constraints

6.4 Design/System Considerations

6.4.1 Do Not Use Machine Learning for the Sake of Using Machine Learning

6.4.2 Learning to Learn

6.4.3 Prediction Time

6.5 Applications/Examples

6.5.1 Curriculum Development

6.5.2 Customized Education Planning

6.5.3 Personalized Rehearsing

6.6 Test and Configuration

6.7 Summary

7: Testing and Configuration

7.1 Introduction

7.2 General Considerations

7.2.1 Data-Ops

7.2.2 Text Analytics and Immunological Data

7.2.3 Text Analytics and Cybersecurity

7.2.4 Data-Ops and Testing

7.3 Machine Learning Aspects

7.4 Design/System Considerations

7.5 Applications/Examples

7.6 Test and Configuration

7.7 Summary

Index

About the Author.

Notes:

Includes index.

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9781000796353

1000796353

9781003338222

1003338224

9781000793581

1000793583

9788770223423

8770223424

OCLC:

1244622420