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This chapter offers a brief introduction to statistical text processing. The Internet is predominantly a vast collection of more or less unclassified text. In order to access such data, numerous techniques have been devised to assign systematic meaning to unstructured text. The chapter seeks to elaborate several of the available techniques to make use of unclassified data. It first presents a small running example, and elaborates how to perform large-scale text operations in R. The chapter introduces the tm package that allows the organization and preparation of text and also provides the infrastructure for the analytical packages. In terms of the techniques that are presented in order to make sense of unstructured text data, the chapter presents supervised methods. The chapter introduces the RTextTools package which provides a wrapper to a number of the available packages. A second approach to classifying text is presented in the chapter-unsupervised classifiers.
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