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First Elements on Knowledge Discovery Guided by Domain Knowledge (KDDK)

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Concept Lattices and Their Applications (CLA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4923))

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Abstract

In this paper, we present research trends carried out in the Orpailleur team at loria, showing how knowledge discovery and knowledge processing may be combined. The knowledge discovery in databases process (kdd) consists in processing a huge volume of data for extracting significant and reusable knowledge units. From a knowledge representation perspective, the kdd process may take advantage of domain knowledge embedded in ontologies relative to the domain of data, leading to the notion of “knowledge discovery guided by domain knowledge” or kddk. The kddk process is based on the classification process (and its multiple forms), e.g. for modeling, representing, reasoning, and discovering. Some applications are detailed, showing how kddk can be instantiated in an application domain. Finally, an architecture of an integrated kddk system is proposed and discussed.

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Authors and Affiliations

  1. LORIA (CNRS – INRIA – Universités de Nancy), Équipe Orpailleur, Bâtiment B, BP 239, F-54506 Vandœuvre-lès-Nancy cedex, France

    Jean Lieber, Amedeo Napoli, Laszlo Szathmary & Yannick Toussaint

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  1. Jean Lieber
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  2. Amedeo Napoli
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  3. Laszlo Szathmary
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  4. Yannick Toussaint
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Sadok Ben Yahia Engelbert Mephu Nguifo Radim Belohlavek

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Lieber, J., Napoli, A., Szathmary, L., Toussaint, Y. (2008). First Elements on Knowledge Discovery Guided by Domain Knowledge (KDDK). In: Yahia, S.B., Nguifo, E.M., Belohlavek, R. (eds) Concept Lattices and Their Applications. CLA 2006. Lecture Notes in Computer Science(), vol 4923. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78921-5_2

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  • DOI: https://doi.org/10.1007/978-3-540-78921-5_2

  • Publisher Name: Springer, Berlin, Heidelberg

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