Abstract
Data Mining and Knowledge Discovery is a young but vigorously growing research area. Its aim is to discover structure or knowledge in databases. It comprises a wide variety of algorithms and techniques for towards this goal.
One of the main challenges in building a data mining system is the flexibility necessary both to support the current variety of algorithms and to extend it easily with new kinds of data mining algorithms. In the Keso project this challenge is met by basing the system on an Inductive Query Language.
This research is supported by ESPRIT under contract 20.596
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Siebes, A. (1996). Data Mining and the Keso project. In: Jeffery, K.G., Král, J., Bartošek, M. (eds) SOFSEM'96: Theory and Practice of Informatics. SOFSEM 1996. Lecture Notes in Computer Science, vol 1175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0037403
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DOI: https://doi.org/10.1007/BFb0037403
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