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Natural Language Processing with Java

You're reading from   Natural Language Processing with Java Techniques for building machine learning and neural network models for NLP

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Product type Paperback
Published in Jul 2018
Publisher
ISBN-13 9781788993494
Length 318 pages
Edition 2nd Edition
Languages
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Authors (2):
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Ashish Bhatia Ashish Bhatia
Author Profile Icon Ashish Bhatia
Ashish Bhatia
Richard M. Reese Richard M. Reese
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Richard M. Reese
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Toc

Table of Contents (14) Chapters Close

Preface 1. Introduction to NLP FREE CHAPTER 2. Finding Parts of Text 3. Finding Sentences 4. Finding People and Things 5. Detecting Part of Speech 6. Representing Text with Features 7. Information Retrieval 8. Classifying Texts and Documents 9. Topic Modeling 10. Using Parsers to Extract Relationships 11. Combined Pipeline 12. Creating a Chatbot 13. Other Books You May Enjoy

Using extracted relationships


Extracted relationships can be used for a number of purposes, including:

  • Building knowledge bases
  • Creating directories
  • Product searches
  • Patent analysis
  • Stock analysis
  • Intelligence analysis

An example of how relationships can be presented is illustrated by Wikipedia's infobox, as shown in the following screenshot. This infobox is for the entry Oklahoma and contains relationship types such as Official language, Capital, and details about its area:

There are many databases built using Wikipedia that extract relationships and information, such as:

  • Resource Description Framework (RDF): This uses triples such as Yosemite-location-California, where the location is the relation. This can be found at http://www.w3.org/RDF/.
  • DBpedia: This holds over one billion triples and is an example of a knowledge base created from Wikipedia. This can be found at https://wiki.dbpedia.org/about.

Another simple but interesting example is the infobox that is presented when a Google search of planet...

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