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  • Book Overview & Buying Mastering Text Mining with R
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Mastering Text Mining with R

Mastering Text Mining with R

By : KUMAR ASHISH
2.4 (11)
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Mastering Text Mining with R

Mastering Text Mining with R

2.4 (11)
By: KUMAR ASHISH

Overview of this book

Text Mining (or text data mining or text analytics) is the process of extracting useful and high-quality information from text by devising patterns and trends. R provides an extensive ecosystem to mine text through its many frameworks and packages. Starting with basic information about the statistics concepts used in text mining, this book will teach you how to access, cleanse, and process text using the R language and will equip you with the tools and the associated knowledge about different tagging, chunking, and entailment approaches and their usage in natural language processing. Moving on, this book will teach you different dimensionality reduction techniques and their implementation in R. Next, we will cover pattern recognition in text data utilizing classification mechanisms, perform entity recognition, and develop an ontology learning framework. By the end of the book, you will develop a practical application from the concepts learned, and will understand how text mining can be leveraged to analyze the massively available data on social media.
Table of Contents (9 chapters)
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Chapter 3. Categorizing and Tagging Text

In corpus linguistics, text categorization or tagging into various word classes or lexical categories is considered to be the second step in NLP pipeline after tokenization. We have all studied parts of speech in our elementary classes; we were familiarized with nouns, pronouns, verbs, adjectives, and their utility in English grammar. These word classes are not just the salient pillars of grammar, but also quite pivotal in many language processing activities. The process of categorizing and labeling words into different parts of speeches is known as parts of speech tagging or simply tagging.

The goal of this chapter is to equip you with the tools and the associated knowledge about different tagging, chunking, and entailment approaches and their usage in natural language processing.

Earlier chapters focused on basic text processing; this chapter improvises on those concepts to explain the different approaches of tagging texts into lexical...

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Mastering Text Mining with R
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