Information that allow a visual representation

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

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 methods...
View Full Document

{[ snackBarMessage ]}

Ask a homework question - tutors are online