Following the knowledge discovery process model

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Unformatted text preview: xtract data from texts. To the extracted data then data mining algorithms can be applied (see Nahm & Mooney (2002); Gaizauskas (2003)). Text Mining = KDD Process. Following the knowledge discovery process model (crispdm and CRISP99 1999), we frequently find in literature text mining as a process with a series of partial steps, among other things also information extraction as well as the use of data mining or statistical procedures. Hearst summarizes this in Hearst (1999) in a general manner as the extraction of not yet discovered information in large collections of texts. Also Kodratoff (1999) and Gomez in Hidalgo (2002) consider text mining as process orientated approach on texts. In this article, we consider text mining mainly as text data mining. Thus, our focus is on methods that extract useful patterns from texts in order to, e.g., categorize or structure text collections or to extract useful information. 1.4 Related Research Areas Current research in the area of text mining tackles problems of text representation, classification, clustering, information extraction or the search for and mode...
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This note was uploaded on 06/19/2011 for the course IT 2258 taught by Professor Aymenali during the Summer '11 term at Abu Dhabi University.

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