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Hands-On Natural Language Processing with Python

You're reading from   Hands-On Natural Language Processing with Python A practical guide to applying deep learning architectures to your NLP applications

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Product type Paperback
Published in Jul 2018
Publisher Packt
ISBN-13 9781789139495
Length 312 pages
Edition 1st Edition
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Authors (5):
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Rajalingappaa Shanmugamani Rajalingappaa Shanmugamani
Author Profile Icon Rajalingappaa Shanmugamani
Rajalingappaa Shanmugamani
Chaitanya Joshi Chaitanya Joshi
Author Profile Icon Chaitanya Joshi
Chaitanya Joshi
Auguste Byiringiro Auguste Byiringiro
Author Profile Icon Auguste Byiringiro
Auguste Byiringiro
Rajesh Arumugam Rajesh Arumugam
Author Profile Icon Rajesh Arumugam
Rajesh Arumugam
Karthik Muthuswamy Karthik Muthuswamy
Author Profile Icon Karthik Muthuswamy
Karthik Muthuswamy
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Table of Contents (15) Chapters Close

Preface 1. Getting Started 2. Text Classification and POS Tagging Using NLTK FREE CHAPTER 3. Deep Learning and TensorFlow 4. Semantic Embedding Using Shallow Models 5. Text Classification Using LSTM 6. Searching and DeDuplicating Using CNNs 7. Named Entity Recognition Using Character LSTM 8. Text Generation and Summarization Using GRUs 9. Question-Answering and Chatbots Using Memory Networks 10. Machine Translation Using the Attention-Based Model 11. Speech Recognition Using DeepSpeech 12. Text-to-Speech Using Tacotron 13. Deploying Trained Models 14. Other Books You May Enjoy

Text summarization

Text summarization is the process of transforming an input document into a short summary, to help us understand the main content of the document in a short amount of time. Fundamentally, there are two types of summarization. One of them is extractive summarization and the other is abstractive summarization. We will briefly look at descriptions of these types of summaries.

Extractive summarization

In this type of summarization, the important phrases or keywords in a document are extracted and concatenated to get a short summary.

The main advantage is that it is simple and robust, since the extracted text is taken directly from the document. The disadvantage of this method is that we may not be able to obtain...

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