Ashish Kumar - Mastering Text Mining with R
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Master text-taming techniques and build effective text-processing applications with R
About This Book
- Gain in-depth understanding of the text mining process with lucid implementation in the R language
- Example-rich guide that lets you gain high-quality information from text data
Who This Book Is For
If you are an R programmer, analyst, or data scientist who wants to gain experience in performing text data mining and analytics with R, then this book is for you. Exposure to working with statistical methods and language processing would be helpful.
What You Will Learn
- Get acquainted with some of the highly efficient R packages such as OpenNLP and RWeka to perform various steps in the text mining process
- Access and manipulate data from different sources such as JSON and HTTP
- Process text using regular expressions
- Get to...
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Copyright 2016 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: December 2016
Production reference: 1231216
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-1-78355-181-1
www.packtpub.com
Authors
Ashish Kumar
Avinash Paul
Reviewers
Dmitry Grapov
Ashraf Uddin
Commissioning Editor
Kartikey Pandey
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Prachi Bisht
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Cover Work
Shraddha Falebhai
Ashish Kumar is an IIM alumnus and an engineer at heart. He has extensive experience in data science, machine learning, and natural language processing having worked at organizations, such as McAfee-Intel, an ambitious data science startup Volt consulting), and presently associated to the software and research lab of a leading MNC. Apart from work, Ashish also participates in data science competitions at Kaggle in his spare time.
Avinash Paul is a programming language enthusiast, loves exploring open sources technologies and programmer by choice. He has over nine years of programming experience. He has worked in Sabre Holdings , McAfee , Mindtree and has experience in data-driven product development, He was intrigued by data science and data mining while developing niche product in education space for a ambitious data science start-up. He believes data science can solve lot of societal challenges. In his spare time he loves to read technical books and teach underprivileged children back home.
I would like to thank my mother, Anthony Mary, without her continuous support and encouragement I never would have been able to achieve my goals.
Dmitry Grapov received his PhD in analytical chemistry with emphasis in biotechnology in 2012 from the University of California, Davis. He currently works as a data scientist at CDS- Creative Data Solutions (http://createdatasol.com/) specializing in R programming, machine learning, and data visualization.
Ashraf Uddin has been pursuing PhD at Department of Computer Science, South Asian University (SAU) since July 2013. Before joining PhD, he completed MCA from SAU in June, 2013 (www.bit.ly/siteAshraf). He obtained his B.Sc. in Mathematics from the Department of Mathematics, University of Dhaka. He has been working in the area of Scientometrics, Text Data Mining, and Information Extraction.
He has published many journal and conference papers in the area of Scientometrics and Text Analytics. He has also authored a book titled Applied Information Extraction and Sentiment Analysis.
I am grateful to my supervisors Dr Pranab Kumar Muhuri and Dr Vivek Kumar Singh for their unconditional support. I also acknowledge my colleagues Rajesh Piryani and Sumit Kumar Banshal for their inspiration and help in the process.
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Text Mining 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.
Our aim in this book is to provide you the information that you will use to develop a practical application from the concepts learned and you will understand how text mining can be leveraged to analyze the massively available data on social media.
We hope you'll get as much from reading this book as we did from writing it.
, Statistical Linguistics with R , covers the basics of statistical analysis, which forms the basis of computational linguistic. This chapter also discusses about various R packages for text mining and their utilities.
, Processing Text , intends to guide readers in handling textual data, right from scratch. Accessing the data from various sources, cleansing texts using Regular expressions, stop words, and help develop skills to process raw texts effectively using R language.
, Categorizing and Tagging Text , empowers the readers to categorize the texts into different word classes or lexical categories.
, Dimensionality Reduction , covers in detail, the various dimensionality reduction methods that can be applied on text data and extending the concept to extract contexts from data in the next chapter.
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