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arXiv:0807.2569stat.ML

Text Data Mining: Theory and Methods

Jeffrey Solka

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Abstract

This paper provides the reader with a very brief introduction to some of the theory and methods of text data mining. The intent of this article is to introduce the reader to some of the current methodologies that are employed within this discipline area while at the same time making the reader aware of some of the interesting challenges that remain to be solved within the area. Finally, the articles serves as a very rudimentary tutorial on some of techniques while also providing the reader with a list of references for additional study.

arXiv comments
Published in at http://dx.doi.org/10.1214/07-SS016 the Statistics Surveys (http://www.i-journals.org/ss/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Journal reference
Statistics Surveys 2008, Vol. 2, 94-112
DOI
doi:10.1214/07-SS016
Subjects
stat.MLMachine Learning (Statistics) cs.IRInformation Retrieval stat.COComputation (Statistics)

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