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A Model of RSDM Implementation

  • María C. Fernández-Baizán
  • Ernestina Menasalvas Ruiz
  • Anita Wasilewska
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1424)

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • María C. Fernández-Baizán
    • 1
    • 2
  • Ernestina Menasalvas Ruiz
    • 1
    • 2
  • Anita Wasilewska
    • 1
    • 2
  1. 1.Departamento de Lenguajes y Sistemas Informáticos e Ingenieía del SoftwareFacultad de InformáticaMadrid
  2. 2.Department of Computer ScienceState University of New YorkStony Brook NY

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