Functional Applications of Text Analytics Systems.

This clearly written text explains the functional applications of search, translation, optimization, and learning with regard to text analytics.

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Bibliographic Details
Superior document:River Publishers Series in Document Engineering Series
:
TeilnehmendeR:
Place / Publishing House:Aalborg : : River Publishers,, 2021.
Ã2021.
Year of Publication:2021
Edition:1st ed.
Language:English
Series:River Publishers Series in Document Engineering Series
Online Access:
Physical Description:1 online resource (290 pages)
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Table of 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.