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Python Natural Language Processing

You're reading from   Python Natural Language Processing Advanced machine learning and deep learning techniques for natural language processing

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787121423
Length 486 pages
Edition 1st Edition
Languages
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Author (1):
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Jalaj Thanaki Jalaj Thanaki
Author Profile Icon Jalaj Thanaki
Jalaj Thanaki
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Toc

Table of Contents (13) Chapters Close

Preface 1. Introduction FREE CHAPTER 2. Practical Understanding of a Corpus and Dataset 3. Understanding the Structure of a Sentences 4. Preprocessing 5. Feature Engineering and NLP Algorithms 6. Advanced Feature Engineering and NLP Algorithms 7. Rule-Based System for NLP 8. Machine Learning for NLP Problems 9. Deep Learning for NLU and NLG Problems 10. Advanced Tools 11. How to Improve Your NLP Skills 12. Installation Guide

Discourse integration

Discourse integration is closely related to pragmatics. Discourse integration is considered as the larger context for any smaller part of NL structure. NL is so complex and, most of the time, sequences of text are dependent on prior discourse.

This concept occurs often in pragmatic ambiguity. This analysis deals with how the immediately preceding sentence can affect the meaning and interpretation of the next sentence. Here, context can be analyzed in a bigger context, such as paragraph level, document level, and so on.

Applications

Concepts of discourse integration have been used by following NLP applications:

  • This concept often used in NLG applications.
  • Chatbots, which are developed to deliver generalized...
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