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 classiffication and string kernels. (authors' abstract)
| Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:3978 |
| Date | 31 March 2008 |
| Creators | Meyer, David, Hornik, Kurt, Feinerer, Ingo |
| Publisher | American Statistical Association |
| Source Sets | Wirtschaftsuniversität Wien |
| Language | English |
| Detected Language | English |
| Type | Article, PeerReviewed |
| Format | application/pdf |
| Rights | Creative Commons: Attribution 3.0 Austria |
| Relation | http://www.jstatsoft.org/v25/i05, http://www.foastat.org/, https://www.jstatsoft.org/about/editorialPolicies#openAccessPolicy, http://epub.wu.ac.at/3978/ |
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