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  • Book Overview & Buying Turning Text into Gold: Taxonomies and Textual Analytics
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Turning Text into Gold: Taxonomies and Textual Analytics

Turning Text into Gold: Taxonomies and Textual Analytics

By : Bill Inmon
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Turning Text into Gold: Taxonomies and Textual Analytics

Turning Text into Gold: Taxonomies and Textual Analytics

4.3 (4)
By: Bill Inmon

Overview of this book

With businesses operating round the clock, a large amount of data gets generated. This data can be efficiently converted into useful knowledge that can take your business to a higher level. This book introduces you to the concept of taxonomies and how they are used to simplify and understand the text. You'll explore how to use taxonomies for textual analytics. It begins with a quick history of taxonomies and their earliest usage. You’ll learn about the different types of taxonomies (recursive, networked, hierarchical, and so on). You'll also learn about ontologies and understand how the ontology becomes a bridge between the worlds of technology and business and commerce. The later chapters of the book show how to find the taxonomies that you need for successful textual analytics, update your taxonomies to include the constantly-changing language, and extract meaningful information from raw text using different tools, such as textual disambiguation, document fracturing, and so on. By the end of this book, you’ll be able to utilize the various aspects of taxonomies for efficient textual analysis.
Table of Contents (20 chapters)
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1
Introduction
5
4: Ontologies
7
6: Changing Taxonomies
9
8: Taxonomies and Data Models
10
9: Types of Textual Data
17
16: Airline Analytics
18
Glossary
19
References
20
Index

Inline Contextualization

For structured, predictable text, it is possible to use inline contextualization to determine the meaning of a word or phrase. In inline contextualization, a beginning delimiter and an ending delimiter determine the context of a word or phrase. Here is an example of inline contextualization:

Image317661.jpg

The example shows that the raw text identifies a gentleman known as Bill Inmon. The beginning delimiter is “the undersigned” and the ending delimiter is “has paid”. Everything between the beginning delimiter and the ending delimiter is the “owner”.

The applicability of inline contextualization is limited to structured textual information.

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Turning Text into Gold: Taxonomies and Textual Analytics
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