Abstract
This paper tackles the problem of knowledge discovery in text collections and the dynamic display of the discovered knowledge. We claim that these two problems are deeply interleaved, and should be considered together. The contribution of this paper is fourfold: (1) description of the properties needed for a high level representation of concept relations in text (2) a stochastic measure for a fast evaluation of dependencies between concepts (3) a visualization algorithm to display dynamic structures and (4) a deep integration of discovery and knowledge visualization, i.e. the placement of nodes and edges automatically guides the discovery of knowledge to be displayed. The resulting program has been tested using two specific data sets based on the specific domains of molecular biology and WWW howtos.
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© 2002 Springer-Verlag Berlin Heidelberg
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Dubois, V., Quafafou, M. (2002). Incremental and Dynamic Text Mining. In: Hacid, MS., Raś, Z.W., Zighed, D.A., Kodratoff, Y. (eds) Foundations of Intelligent Systems. ISMIS 2002. Lecture Notes in Computer Science(), vol 2366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48050-1_30
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DOI: https://doi.org/10.1007/3-540-48050-1_30
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