A new rough sets model based on database systems

Authors:
Xiaohua Tony Hu;T. Y. Lin;Jianchao Han
Affiliations:
College of Information Science and Technology, Drexel University, Philadelphia, PA;Dept. of Computer Science, San Jose State University, San Jose, CA;Dept. of Computer Science, California State University, Dominguez Hills, CA
Venue:
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Year:
2003

Citing 5
Cited 5

Variable precision rough set model

Journal of Computer and System Sciences
New Techniques for Data Reduction in a Database System for Knowledge Discovery Applications

Journal of Intelligent Information Systems
Feature Selection Using Rough Sets Theory

ECML '93 Proceedings of the European Conference on Machine Learning
Data mining, rough sets and granular computing

Data mining, rough sets and granular computing
GRS: a generalized rough sets model

Data mining, rough sets and granular computing

Attribute set dependence in reduct computation

Transactions on computational science II
An agent model for rough classifiers

Applied Soft Computing
Rule extraction based on rough fuzzy sets in fuzzy information systems

Transactions on computational collective intelligence III
Attribute set dependence in apriori-like reduct computation

RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Survey paper: Knowledge discovery in clinical decision support systems for pain management: A systematic review

Artificial Intelligence in Medicine

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we present a new rough sets model based on database systems. We borrow the main ideas of the original rough sets theory and redefine them based on the database theory to take advantage of the very efficient set-oriented database operation. We present a new set of algorithms to calculate core, reduct based on our new database based rough set model. Almost all the operations used in generating core, reduct in our model can be performed using the database set operations such as Count, Projection. Our new rough sets model is designed based on database set operations, compared with the traditional rough set models, ours is very efficient and scalable.