Abstract
The first part of this paper will give a general view of Knowledge Discovery in Data (KDD) in order to insist on how much it differs from the fields it stems from, and in some cases, how much it opposes them.
The second part will a definition of Knowledge Discovery in Texts (KDT), as opposed to what is known presently under the name of information retricval, information extraction, or knowledge extraction. I will provide an example of a real-life set of rules obtained by what I want to define as KDT techniques.
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Kodratoff, Y. (1999). Knowledge discovery in texts: A definition, and applications. In: Raś, Z.W., Skowron, A. (eds) Foundations of Intelligent Systems. ISMIS 1999. Lecture Notes in Computer Science, vol 1609. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095087
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DOI: https://doi.org/10.1007/BFb0095087
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