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Topic Map Generation Using Text Mining

Paper, was published by Gerhard Heyer, Karsten Böhm, Uwe Quasthoff, and Christian Wolff at 2002-06-28

This paper describes an infrastructure for text mining which uses collocation analysis.

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Starting from text corpus analysis with linguistic and statistical analysis algorithms, an infrastructure for text mining is described which uses collocation analysis as a central tool. This text mining method may be applied to different domains as well as languages. Some examples taken form large reference databases motivate the applicability to knowledge management using declarative standards of information structuring and description. The ISO/IEC Topic Map standard is introduced as a candidate for rich metadata description of information resources and it is shown how text mining can be used for automatic topic map generation.


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Topic Maps is the only formal semantic model which is optimized for humans, not for computers. Applications and web portals based on Topic Maps are easy to use, without limitations for flexibility and creativity.

Benjamin Bock
Ruby Topic Maps
Topic Maps Lab auf der Cebit 2011

Graduate from the Topic Maps Lab