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Integrating RDMS and Data Mining Capabilities Using Rough Sets

  • María C. Fernandez-Baizán
  • Ernestina Menasalvas Ruiz
  • José M. Peña Sánchez
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 39)

Abstract

Mining information from large databases has been recognized as a key research topic in database systems. The explosive growth of databases has made neccesary to discover techniques and tools to transform the huge amount of stored data, into useful information. Rough Set Theory [17] has been applied since its very beginning to different application areas. This chapter presents an integration of Relational DataBase Management technology with Rough Sets Theory to show how the algorithms can be successfully translated into SQL and used as a powerful tool for knowledge discovery.

As a consecuence, a system has been designed and implemented in our research, called RSDM (Rough Set Data Miner), its architecture as well as its main properties will be further described in this chapter.

Keywords

Association Rule Knowledge Discovery Mining Association Rule Decision Attribute Relational Database Management System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • María C. Fernandez-Baizán
    • 1
  • Ernestina Menasalvas Ruiz
    • 1
  • José M. Peña Sánchez
    • 1
  1. 1.Departamento de Lenguajes y Sistemas Informáticos e Ingeniería del Software, Facultad de InformáticaCampus de MontegancedoMadridSpain

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