Title :
Study on Incremental Data Mining Based on Rough Set Theory
Author :
Lv, ShanGuo ; Chen, HongLi
Author_Institution :
Sch. of Software, East China Jongtong Univ., Nanchang, China
Abstract :
This paper presented an incremental data mining algorithm for mining simplified rules. By using a method of the attribute´s number increased progressively to check the superfluity of the decision rules. RIDA makes full use of mined rules to mine decision rules from new instance. This algorithm has a high efficiency with simple calculation compared with classical Rough set mining algorithm. And it has verified feasibility and validity of this algorithm through the instance analysis.
Keywords :
data mining; rough set theory; RIDA; incremental data mining; rough set mining algorithm; rough set theory; Data mining; Data security; Decision making; Informatics; Information security; Information systems; Information technology; Machine learning; Partitioning algorithms; Set theory; decision rule; incremental mining; rough set theory;
Conference_Titel :
Intelligent Information Technology and Security Informatics (IITSI), 2010 Third International Symposium on
Conference_Location :
Jinggangshan
Print_ISBN :
978-1-4244-6730-3
Electronic_ISBN :
978-1-4244-6743-3
DOI :
10.1109/IITSI.2010.168
