@article{JSSv025i05, title={Text Mining Infrastructure in R}, volume={25}, url={https://www.jstatsoft.org/index.php/jss/article/view/v025i05}, doi={10.18637/jss.v025.i05}, abstract={During the last decade text mining has become a widely used discipline utilizing statistical and machine learning methods. We present the <strong>tm</strong> 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.}, number={5}, journal={Journal of Statistical Software}, author={Feinerer, Ingo and Hornik, Kurt and Meyer, David}, year={2008}, pages={1–54} }