Abstract
Today’s Data Base Management Systems do not provide functionality to extract potentially hidden knowledge in data. This problem gave rise in the 80’s to a new research area called Knowledge Discovery in Data Bases (KDD). In spite the great amount of research that has been done in the past 10 years, there is no uniform mathematical model to describe various techniques of KDD. The main goal of this paper is to describe such a model. The Model integrates in an uniform framework various Rough Sets Techniques with standard, non Rough Sets based techniques of KDD.
The Model has been already partially implemented in RSDM (Rough Set Data Miner) and we plan to complete the implementation by integrating all the operations in the code of database management systems. Operations that are defined in the paper have successfully been implemented as part of RSDM.
This work is supported by the Spanish Ministry of Education under project PB95-0301
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Fernández-Baizán, M.C., Ruiz, E.M., Wasilewska, A. (1998). A Model of RSDM Implementation. In: Polkowski, L., Skowron, A. (eds) Rough Sets and Current Trends in Computing. RSCTC 1998. Lecture Notes in Computer Science(), vol 1424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-69115-4_26
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DOI: https://doi.org/10.1007/3-540-69115-4_26
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