Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Text Mining Infrastructure in R | Feinerer | Journal of Statistical Software
Authors: Ingo Feinerer, Kurt Hornik, David Meyer
Title: Text Mining Infrastructure in R
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.

Page views:: 122995. Submitted: 2007-09-05. Published: 2008-03-31.
Paper: Text Mining Infrastructure in R     Download PDF (Downloads: 118094)
Supplements:
tm_0.3.tar.gz: R source package Download (Downloads: 6811; 569KB)
v25i05.R: R example code from the paper Download (Downloads: 11524; 25KB)
DOI: 10.18637/jss.v025.i05

by
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.