Variable precision rough set model
Journal of Computer and System Sciences
Enhancements to the data mining process
Enhancements to the data mining process
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
An Overview of Knowledge Discovery in Database: Recent Progress and Challenges
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
High Frequent Value Reduct in Very Large Databases
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
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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.