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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
Author Profile Icon Richard M. Reese
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

TF-IDF weighting


TF-IDF combines the approaches of term frequency (TF) and inverse document frequency (IDF) to generate a weight for each term in a document, and it is done using the following formula:

In other words, it assigns a weight to term t in document d as follows:

  • If term t occurs many times in a few documents, it will be the highest
  • If term t occurs a small number of times in a document, it will be lower
  • If term t occurs in all documents, it will be the lowest
  • If term t occurs in no documents, it will be 0
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