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Book Description

In our distant past, we attempted to create wealth by turning everyday substances into gold. This was early alchemy, and ultimately it did not work. But the world has changed. Today we have a type of "modern alchemy" that really can create gold. We can transform voluminous text into a wealth of knowledge.

Text is a common fabric of society, yet it is still challenging for our technology to make sense of text. This is where taxonomies can help. In this book, legendary Bill Inmon will introduce you to the concept of taxonomies and how they are used to simplify and understand text. We emphasize the practical aspects of taxonomies, and the subsequent usage of taxonomies as a basis for textual analytics.

This book is for managers who have to deal with text, students of computer science, programmers who need to understand taxonomies, systems analysts who hope to draw business value out of a body of text, and especially those who are struggling to decode data lakes. Hopefully for those individuals (and many more), this book will serve as both an introduction to taxonomies and a guide to how taxonomies can be used to bring text into the realm of corporate decision-making.

This book will introduce you to the world of taxonomies, as well as explore:
  • Simple and complex taxonomies
  • Ontologies
  • Obtaining taxonomies
  • Changing taxonomies
  • Taxonomies and data models
  • Types of textual data
  • Textual analytics.
In addition, several case studies are presented from industries as diverse as banking, call centers, and travel.

Table of Contents

  1. Introduction
  2. 1: Brief History of Taxonomies
    1. Insufficiency of Structured Data
    2. Manual Processing
    3. Evolution of Textual Analytic Technology
  3. 2: Simple Taxonomies
    1. Taxonomy Components
    2. Taxonomies and Language
  4. 3: Complex Taxonomies
    1. Hierarchical Taxonomies
    2. Networked Taxonomies
    3. More Applications of Taxonomies
  5. 4: Ontologies
  6. 5: Obtaining Taxonomies
    1. Curated Taxonomies
    2. Building Your Own Taxonomy
    3. Qualifying the Nouns
  7. 6: Changing Taxonomies
  8. 7: Taxonomies as Databases
    1. MoveRemove Processing
    2. Taxonomy Customization
    3. Word Pairs
    4. Transporting the Taxonomy
  9. 8: Taxonomies and Data Models
  10. 9: Types of Textual Data
  11. 10: Textual Analytics
    1. Document Fracturing
    2. Named Value Processing
    3. Supporting Processes
  12. 11: Stage 1 Processing
    1. Basic Refinements
    2. Custom Variables
    3. Inline Contextualization
    4. Proximity Analysis and Resolution
    5. Stop Word Processing
    6. Associative Word Processing
    7. Homographic Resolution
    8. Alternate Spelling
    9. Acronym Resolution
    10. Stemming
    11. Date Normalization
  13. 12: Stage 2 Processing
    1. Sentiment Analysis
    2. Negativity Analysis
    3. Medical Records
  14. 13: Banking Analytics
    1. Publicly Available Banking Data
    2. Comments Collected
    3. Textual Disambiguation
    4. Secondary Inference Analysis
    5. Visualization
    6. Interpreting the Dashboard
    7. Considering a Single Bank
  15. 14: Call Center Analytics
    1. What the Call Center Hears
    2. Processing the Narrative
    3. Examining the Dashboard
    4. Getting to Visualization
  16. 15: Hospitality Analytics
    1. Voice of the Customer
    2. Analyzing Restaurant Feedback
  17. 16: Airline Analytics
  18. Glossary
  19. References
  20. Index
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