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The Natural Language Processing Workshop

You're reading from  The Natural Language Processing Workshop

Product type Book
Published in Aug 2020
Publisher Packt
ISBN-13 9781800208421
Pages 452 pages
Edition 1st Edition
Languages
Authors (6):
Rohan Chopra Rohan Chopra
Profile icon Rohan Chopra
Aniruddha M. Godbole Aniruddha M. Godbole
Profile icon Aniruddha M. Godbole
Nipun Sadvilkar Nipun Sadvilkar
Profile icon Nipun Sadvilkar
Muzaffar Bashir Shah Muzaffar Bashir Shah
Profile icon Muzaffar Bashir Shah
Sohom Ghosh Sohom Ghosh
Profile icon Sohom Ghosh
Dwight Gunning Dwight Gunning
Profile icon Dwight Gunning
View More author details

Table of Contents (10) Chapters

Preface
1. Introduction to Natural Language Processing 2. Feature Extraction Methods 3. Developing a Text Classifier 4. Collecting Text Data with Web Scraping and APIs 5. Topic Modeling 6. Vector Representation 7. Text Generation and Summarization 8. Sentiment Analysis Appendix

Finding Text Similarity – Application of Feature Extraction

So far in this chapter, we have learned how to generate vectors from text. These vectors are then fed to machine learning algorithms to perform various tasks. Other than using them in machine learning applications, we can also perform simple NLP tasks using these vectors. Finding the string similarity is one of them. This is a technique in which we find the similarity between two strings by converting them into vectors. The technique is mainly used in full-text searching.

There are different techniques for finding the similarity between two strings or texts. They are explained one by one here:

  • Cosine similarity: The cosine similarity is a technique to find the similarity between the two vectors by calculating the cosine of the angle between them. As we know, the cosine of a zero-degree angle is 1 (meaning the cosine similarity of two identical vectors is 1), while the cosine of 180 degrees is -1 (meaning...
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The Natural Language Processing Workshop
Published in: Aug 2020 Publisher: Packt ISBN-13: 9781800208421
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