JUCS - Journal of Universal Computer Science 8(6): 623-633, doi: 10.3217/jucs-008-06-0623
Topic Map Generation Using Text Mining
expand article infoKarsten Böhm‡, Gerhard Heyer§, Uwe Quasthoff§, Christian Wolff§
‡ TextTech Ltd., Leipzig, Germany§ Leipzig University, Leipzig, Germany

Corresponding author: Karsten Böhm ( boehm@texttech.de )

© Karsten Böhm, Gerhard Heyer, Uwe Quasthoff, Christian Wolff.
This article is freely available under the J.UCS Open Content License.
Citation: Böhm K, Heyer G, Quasthoff U, Wolff C (2002) Topic Map Generation Using Text Mining. JUCS - Journal of Universal Computer Science 8(6): 623-633. https://doi.org/10.3217/jucs-008-06-0623
Open Access
Abstract
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.
Keywords
topic maps, text mining, corpora, semantic relations, knowledge management