Approach to generating rules for expert systems using rough set theory

Author

Phuong, Nguyen Hoang ; Phong, Le Linh ; Santiprabhob, Pratit ; De Baets, Bernard

Author_Institution

Intelligent Syst. Lab., Assumption Univ., Bangkok, Thailand

Volume

2

fYear

2001

fDate

25-28 July 2001

Firstpage

877

Abstract

The problem of data mining and knowledge discovery as generating rules from databases has become a great research interest of many researchers. Many methods such as induction learning, ID3 etc., have been developed. A a new approach based on rough set theory has been proposed. Rough set theory was proposed by Zdzislaw Pawlak (1980) to deal with inconsistent problems. Our work is to apply this theory in extracting rules from given medical databases. This results in a set of decision rules, which will be provided for one of our diagnostic systems as a part of its knowledge base

Keywords

data mining; medical diagnostic computing; medical expert systems; medical information systems; rough set theory; very large databases; data mining; decision rules; knowledge acquisition; knowledge base; knowledge discovery; medical databases; medical diagnostic systems; medical expert systems; rough set theory; rule generation; Deductive databases; Diseases; Expert systems; Information systems; Intelligent systems; Knowledge acquisition; Laboratories; Medical diagnostic imaging; Medical expert systems; Set theory;

fLanguage

English

Publisher

ieee

Conference_Titel

IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th

Conference_Location

Vancouver, BC

Print_ISBN

0-7803-7078-3

Type

conf

DOI

10.1109/NAFIPS.2001.944720

Filename

944720