Unformatted text preview: ports the following F1-measures for the CoNLL corpus: person
names 93%, location names 92%, organization names 84%, miscellaneous names
80%. CRFs also have been successfully applied to noun phrase identiﬁcation
(McCallum 2003), part-of-speech tagging (Lafferty et al. 2001), shallow parsing
(Sha & Pereira 2003), and biological entity recognition (Kim et al. 2004).
3.4 Explorative Text Mining: Visualization Methods Graphical visualization of information frequently provides more comprehensive
and better and faster understandable information than it is possible by pure
text based descriptions and thus helps to mine large document collections.
Many of the approaches developed for text mining purposes are motivated
by methods that had been proposed in the areas of explorative data analysis,
information visualization and visual data mining. For an overview of these
areas of research see, e.g., U. Fayyad (2001); Keim (2002). In the following we
will focus on methods that have been speciﬁcally designed for text mining or —
as a subgroup of text mining methods and a typical application of visualization
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