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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

Coding – BoW

I will use the classic song Theme from New York, New York by Frank Sinatra. Its repetition of “New York” is a good choice for NLP. At the time of writing this chapter, the jazz music of the song accompanies the calm and snowy midnight in New York.

“Start spreading the news

You’re leaving today (tell him friend)

I want to be a part of it, New York, New York

Your vagabond shoes, they are longing to stray

And steps around the heart of it, New York, New York”

Let’s learn how to do BoW with Gensim.

Gensim for BoW

Let’s import several modules. The Gensim simple_preprocess function converts a document into a list of tokens. The Gensim Dictionary() class implements the concept of a dictionary in Gensim. It maps a tokenized word to a unique ID. I will also import pprint for prettyprint. It will print output in a prettier form:

import gensimfrom gensim.utils import simple_preprocess
from gensim.corpora...
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