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

Product type Paperback

Published in Oct 2023

Publisher Packt

ISBN-13 9781803244945

Length 310 pages

Edition 1st Edition

Tools

fastText

Concepts

Mobile Application Development

Author (1):

Chris Kuo

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Table of Contents (24) Chapters

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

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23. Other Books You May Enjoy

BERTopic for legal documents

NLP techniques can be applied to the large body of unstructured legal documents. One of the NLP applications is document grouping. Because legal documents can relate to each other in terms of topic of interest, topic modeling techniques can help legal professionals to search documents efficiently.

Background

Search engines in legal databases are transforming to advanced NLP techniques. This technology transformation will save legal professionals’ time and increase their productivity. Let’s see what the challenges are.

Questions

However, legal text processing is a challenging task because of legal-specific terminology. How to apply BERTopic modeling to tag the documents?

NLP solution

The authors of [9] applied BERTopic modeling to legal documents from the US case law dataset. They performed the standard BERTopic modeling procedure with plausible results.

Interpretability is a critical criterion for the results of a topic...

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