Text Mining Infrastructure in<i>R</i>
Journal of Statistical SoftwarePublished 1 January 2008Open access
Ingo Feinerer, Kurt Hornik, David Meyer
Citations1,145
SJR quartileQ1
SJR score3.21
SNIP4.61
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TL;DR
The tm package is presented which provides a framework for text mining applications within R and techniques for count-based analysis methods, text clustering, text classification and string kernels are presented.
Abstract
During the last decade text mining has become a widely used discipline utilizing statistical and machine learning methods. We present the tm package which provides a framework for text mining applications within R. We give a survey on text mining facilities in R and explain how typical application tasks can be carried out using our framework. We present techniques for count-based analysis methods, text clustering, text classification and string kernels.
Keywords
Computer Science
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