Abstract
The subject of this paper is the implementation of knowledge discovery in databases. Specifically, we assess the requirements for interfacing tools to client-server database systems in view of the architecture of those systems and of “knowledge discovery processes”. We introduce the concept of a query frontier of an exploratory process, and propose a strategy based on optimizing the current query frontier rather than individual knowledge discovery algorithms. This approach has the advantage of enhanced genericity and interoperability. We demonstrate a small set of query primitives, and show how one example tool, the well-known decision tree induction algorithm C4.5, can be rewritten to function in this environment.
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© 1998 Springer-Verlag Berlin Heidelberg
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Dewhurst, N., Lavington, S. (1998). Knowledge discovery from client-server databases. In: Żytkow, J.M., Quafafou, M. (eds) Principles of Data Mining and Knowledge Discovery. PKDD 1998. Lecture Notes in Computer Science, vol 1510. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0094832
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DOI: https://doi.org/10.1007/BFb0094832
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