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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

Architecture of the RB system

I will explain the architecture of the RB system by segregating it into three sections:

  • General architecture of RB system as an expert system
  • Practical architecture of the RB system for NLP applications
  • Custom architecture - RB system for NLP applications
  • Apache UIMA (Unstructured Information Management Architecture) the RB system for NLP applications

General architecture of the rule-based system as an expert system

If we described our rule-based system as an expert system, then the architecture of this kind of rule-based system would be the same as in Figure 7.5:

Figure 7.5: Architecture of the RB system, considering it as an expert system

Let's look at each of the components of the architecture...

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