Book Image

Natural Language Processing: Python and NLTK

By : Jacob Perkins, Nitin Hardeniya, Deepti Chopra, Iti Mathur, Nisheeth Joshi
Book Image

Natural Language Processing: Python and NLTK

By: Jacob Perkins, Nitin Hardeniya, Deepti Chopra, Iti Mathur, Nisheeth Joshi

Overview of this book

Natural Language Processing is a field of computational linguistics and artificial intelligence that deals with human-computer interaction. It provides a seamless interaction between computers and human beings and gives computers the ability to understand human speech with the help of machine learning. The number of human-computer interaction instances are increasing so it’s becoming imperative that computers comprehend all major natural languages. The first NLTK Essentials module is an introduction on how to build systems around NLP, with a focus on how to create a customized tokenizer and parser from scratch. You will learn essential concepts of NLP, be given practical insight into open source tool and libraries available in Python, shown how to analyze social media sites, and be given tools to deal with large scale text. This module also provides a workaround using some of the amazing capabilities of Python libraries such as NLTK, scikit-learn, pandas, and NumPy. The second Python 3 Text Processing with NLTK 3 Cookbook module teaches you the essential techniques of text and language processing with simple, straightforward examples. This includes organizing text corpora, creating your own custom corpus, text classification with a focus on sentiment analysis, and distributed text processing methods. The third Mastering Natural Language Processing with Python module will help you become an expert and assist you in creating your own NLP projects using NLTK. You will be guided through model development with machine learning tools, shown how to create training data, and given insight into the best practices for designing and building NLP-based applications using Python. This Learning Path combines some of the best that Packt has to offer in one complete, curated package and is designed to help you quickly learn text processing with Python and NLTK. It includes content from the following Packt products: ? NTLK essentials by Nitin Hardeniya ? Python 3 Text Processing with NLTK 3 Cookbook by Jacob Perkins ? Mastering Natural Language Processing with Python by Deepti Chopra, Nisheeth Joshi, and Iti Mathur
Table of Contents (6 chapters)

Chapter 9. Discourse Analysis – Knowing Is Believing

Discourse analysis is another one of the applications of Natural Language Processing. Discourse analysis may be defined as the process of determining contextual information that is useful for performing other tasks, such as anaphora resolution (AR) (we will cover this section later in this chapter), NER, and so on.

This chapter will include the following topics:

  • Introducing discourse analysis
  • Discourse analysis using Centering Theory
  • Anaphora resolution

Introducing discourse analysis

The word discourse in linguistic terms means language in use. Discourse analysis may be defined as the process of performing text or language analysis, which involves text interpretation and knowing the social interactions. Discourse analysis may involve dealing with morphemes, n-grams, tenses, verbal aspects, page layouts, and so on. Discourse may be defined as the sequential set of sentences.

In most cases, we can interpret the meaning of the...