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Natural Language Processing Fundamentals

You're reading from   Natural Language Processing Fundamentals Build intelligent applications that can interpret the human language to deliver impactful results

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Product type Paperback
Published in Mar 2019
Publisher
ISBN-13 9781789954043
Length 374 pages
Edition 1st Edition
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Authors (2):
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Dwight Gunning Dwight Gunning
Author Profile Icon Dwight Gunning
Dwight Gunning
Sohom Ghosh Sohom Ghosh
Author Profile Icon Sohom Ghosh
Sohom Ghosh
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Table of Contents (10) Chapters Close

Preface 1. Introduction to Natural Language Processing FREE CHAPTER 2. Basic Feature Extraction Methods 3. Developing a Text classifier 4. Collecting Text Data from the Web 5. Topic Modeling 6. Text Summarization and Text Generation 7. Vector Representation 8. Sentiment Analysis Appendix

Introduction

One huge challenge when dealing with text data is that data can be huge in size and can come in various forms, such as documents, emails, and web pages. Reading and understanding such data is a cumbersome task. Also, people tend to be less patient when it comes to reading huge amounts of information; they prefer to consume information in bite-size chunks. For instance, Twitter has doubled its character limit, but it is still only 280 characters. Our interactions over Instagram, Facebook, Snapchat, and other social media platforms have got us accustomed to reading concise text.

Due to this change in habits, there is a need to reduce the volume of content that we ask people to read while still retaining the central ideas of the content. To aid this, content providers sport features such as text summaries that provide users with the gist of information.

Therefore, there is a big business need to automate text summarization. In the coming sections, we will explore text...

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