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The Handbook of NLP with Gensim

You're reading from   The Handbook of NLP with Gensim Leverage topic modeling to uncover hidden patterns, themes, and valuable insights within textual data

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781803244945
Length 310 pages
Edition 1st Edition
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Author (1):
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Chris Kuo Chris Kuo
Author Profile Icon Chris Kuo
Chris Kuo
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Table of Contents (24) Chapters Close

Preface 1. Part 1: NLP Basics
2. Chapter 1: Introduction to NLP FREE CHAPTER 3. Chapter 2: Text Representation 4. Chapter 3: Text Wrangling and Preprocessing 5. Part 2: Latent Semantic Analysis/Latent Semantic Indexing
6. Chapter 4: Latent Semantic Analysis with scikit-learn 7. Chapter 5: Cosine Similarity 8. Chapter 6: Latent Semantic Indexing with Gensim 9. Part 3: Word2Vec and Doc2Vec
10. Chapter 7: Using Word2Vec 11. Chapter 8: Doc2Vec with Gensim 12. Part 4: Topic Modeling with Latent Dirichlet Allocation
13. Chapter 9: Understanding Discrete Distributions 14. Chapter 10: Latent Dirichlet Allocation 15. Chapter 11: LDA Modeling 16. Chapter 12: LDA Visualization 17. Chapter 13: The Ensemble LDA for Model Stability 18. Part 5: Comparison and Applications
19. Chapter 14: LDA and BERTopic 20. Chapter 15: Real-World Use Cases 21. Assessments 22. Index 23. Other Books You May Enjoy

What is cosine similarity?

The similarity of two vectors can be measured using cosine similarity. So, let’s start with vector properties. Given two vectors, one vector can be projected onto another to show “how much” a vector is pointing in the same direction as the other. Figure 5.1 shows a 2D graph of the projection of vector a onto vector b.

Figure 5.1 – The projection of vector a on vector b

Figure 5.1 – The projection of vector a on vector b

It is the shadow of vector a being cast on vector b. If the angle is small, the shadow will be long. It means the two vectors are very close. If the angle is as large as 90 degrees, the shadow is almost 0. It means the two vectors are not related at all. Therefore, the angle between the two vectors can measure the similarity. The length of the shadow is the length of a times the cosine of the angle between the two vectors. We will use the dot product of two vectors to mathematically define the similarity.

The dot product of vectors...

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