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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

Extracting relationships


There are a number of techniques available to extract relationships. These can be grouped as follows:

  • Hand-built patterns
  • Supervised methods
  • Semi-supervised or unsupervised methods
  • Bootstrapping methods
  • Distant supervision methods
  • Unsupervised methods

Hand-built models are used when we have no training data. This can occur with new business domains or entirely new types of projects. These often require the use of rules. A rule might be:

"If the word "actor" or "actress" is used and not the word "movie" or "commercial", then the text should be classified as a play."

However, this approach takes a lot of effort and needs to be adjusted for the actual text in-hand.

If only a little training data is amiable, then the Naive Bayes classifier is a good choice. When more data is available, then techniques such as support vector machine (SVM), regularized logistic regression, and random forest can be used.

Although it is useful to understand these techniques in more detail, we will...

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