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Mastering Text Mining with R

You're reading from Mastering Text Mining with R Extract and recognize your text data

Product type Paperback

Published in Dec 2016

Publisher Packt

ISBN-13 9781783551811

Length 258 pages

Edition 1st Edition

Languages

R

Concepts

Data Mining

Author (1):

KUMAR ASHISH

View More author details

Table of Contents (9) Chapters

Preface

1. Statistical Linguistics with R FREE CHAPTER

2. Processing Text

3. Categorizing and Tagging Text

4. Dimensionality Reduction

5. Text Summarization and Clustering

6. Text Classification

7. Entity Recognition

Index

Language detection

TextCat is a text classification utility. The primary usage of TextCat is language identification. textcat package in R provides wrapper function for n-gram based text categorization and the language detection. It can detect up to 75 languages:

Library(textcat)>my.profiles <- TC_byte_profiles[names(TC_byte_profiles)]
>my.profiles

A textcat profile db of length 75.

> my.text <- c("This book is in English language",
 "Das ist ein deutscher Satz.",
 "Il s'agit d'une phrase française.",
 "Esta es una frase en espa~nol.")
 textcat(my.text, p = my.profiles)
> textcat(my.text, p = my.profiles)

[1] "english" "german"  "french"  "spanish"

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Authors (1)

KUMAR ASHISH

KUMAR ASHISH

Ashish Kumar is a seasoned data science professional, a publisher author and a thought leader in the field of data science and machine learning. An IIT Madras graduate and a Young India Fellow, he has around 7 years of experience in implementing and deploying data science and machine learning solutions for challenging industry problems in both hands-on and leadership roles. Natural Language Procession, IoT Analytics, R Shiny product development, Ensemble ML methods etc. are his core areas of expertise. He is fluent in Python and R and teaches a popular ML course at Simplilearn. When not crunching data, Ashish sneaks off to the next hip beach around and enjoys the company of his Kindle. He also trains and mentors data science aspirants and fledgling start-ups.

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