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A model of RSDM implementation

  • Sistemas Informáticos e Ingeniería del Software
  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

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.

Original languageEnglish
Title of host publicationRough Sets and Current Trends in Computing - 1st International Conference, RSCTC 1998, Proceedings
EditorsLech Polkowski, Andrzej Skowron
PublisherSpringer Verlag
Pages186-193
Number of pages8
ISBN (Print)3540646558, 9783540646556
DOIs
StatePublished - 1998
Event1st International Conference on Rough Sets and Current Trends in Computing, RSCTC 1998 - Warsaw, Poland
Duration: Jun 22 1998Jun 26 1998

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1424
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Conference on Rough Sets and Current Trends in Computing, RSCTC 1998
Country/TerritoryPoland
CityWarsaw
Period06/22/9806/26/98

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