Beschreibung Turning Text into Gold: Taxonomies and Textual Analytics. 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.
Turning Text into Gold: Taxonomies and Textual Analytics ~ Turning Text into Gold: Taxonomies and Textual Analytics (English Edition) eBook: Bill Inmon: : Kindle-Shop
Turning Text into Gold: Taxonomies and Textual Analytics ~ Turning Text into Gold: Taxonomies and Textual Analytics - Ebook written by Bill Inmon. Read this book using Google Play Books app on your PC, android, iOS devices. Download for offline reading, highlight, bookmark or take notes while you read Turning Text into Gold: Taxonomies and Textual Analytics.
Turning Text into Gold: Taxonomies and Textual Analytics ~ In his book, Turning Text into Gold, Bill Inmon examines various topics related to text modeling and NLP. Namely, he looks at taxonomies, ontologies, databases briefly, text data types, text analytics, two different levels of text processing, and four different use cases of text analytics across the industry. His overall style is high-level, while the book is rich with diagrams to clarify the .
Turning text into gold : taxonomies and textual analytics ~ Get this from a library! Turning text into gold : taxonomies and textual analytics. [William H Inmon] -- Annotation 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 .
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4: Ontologies - Turning Text into Gold: Taxonomies and ~ The ontology in the context of textual analytics, though, has a different and very precise definition. An ontology is a logical relationship of elements participating in a taxonomy. These incarnations of ontologies are only distantly related to the ontologies that are found in philosophy.
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Turning Text into Gold: Taxonomies and Textual Analytics ~ 6: Changing Taxonomies Consider the word âblogâ. If you would have said the word âblogâ to anyone in the 1990âs, nobody would have known what you were talking about. Today, ⊠- Selection from Turning Text into Gold: Taxonomies and Textual Analytics [Book]
Turning Text into Gold - Technics Pub ~ Turning Text into Gold Taxonomies and Textual Analytics 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 âmodern alchemyâ that really can create gold. We can transform voluminous text into a wealth of knowledge. Text is a common fabric of .
Taxonomy Components - Turning Text into Gold: Taxonomies ~ The specific examples of text include Ford, Chevrolet, Porsche, Volkswagen, Toyota, Honda, and Kia. The unnamed discriminator of this taxonomy is that all elements need to be a type of car. It would be inappropriate to put a Sherman tank, Boeing 747, Navajo blanket, bull elephant, or basking shark into this taxonomy because they are not types of cars.
Bill Inmon - Wikipedia ~ Textual disambiguation applies context to raw text and reformats the raw text and context into a standard data base format. Once raw text is passed through textual disambiguation, it can easily and efficiently be accessed and analyzed by standard business intelligence technology. Textual disambiguation is accomplished through the execution of textual ETL. Publications. Inmon has published more .
Audiobooks written by Bill Inmon / Audible ~ Turning Text into Gold; By: Bill Inmon Narrated by: Lou Lambert Length: 1 hr and 48 mins Unabridged Overall 4 out of 5 stars 4 Performance 4.5 out of 5 stars 4 Story 4 out of 5 stars 4 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, Bill Inmon will introduce you to the concept of .
TextAnalysisTool.NET ~ Download. TextAnalysisTool.NET.zip. Includes: Version 2018-11-20 for .NET 4+ (32- and 64-bit) Version 2013-05-07 for .NET 2+ (32- and 64-bit) Version 2006-12-04 for .NET 1.1+ (32-bit only) Version 2001-12-28 for x86 (32-bit only) License: MIT Overview. The Problem: For those times when you have to analyze a large amount of textual data, picking out the relevant line(s) of interest can be quite .
Text mining - Wikipedia ~ Text analytics. The term text analytics describes a set of linguistic, statistical, and machine learning techniques that model and structure the information content of textual sources for business intelligence, exploratory data analysis, research, or investigation. The term is roughly synonymous with text mining; indeed, Ronen Feldman modified a 2000 description of "text mining" in 2004 to .
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