Title :
Distribution Reduction in Inconsistent Interval Ordered Information Systems Based on Dominance Relations
Author :
Hong Wang ; Ming-gang Du
Author_Institution :
Coll. of Math. & Comput. Sci., Shanxi Normal Univ., Linfen, China
Abstract :
Rough sets serves as a tool for data analysis and knowledge discovery from data databases. Attribute reduction is a basic issue in knowledge representation and data mining. This paper deals with distribution reduction in an inconsistent interval ordered information systems. The distribution reduction and maximum distribution reduction are proposed in inconsistent interval ordered information systems. Moreover, properties and relationship between them are discussed. Furthermore, judgement theorem and discernibility matrix are obtained, from which approaches to distribution reductions can be provided in inconsistent interval ordered information systems.
Keywords :
data mining; knowledge representation; matrix algebra; rough set theory; attribute reduction; data analysis; data databases; data mining; discernibility matrix; dominance relations; inconsistent interval ordered information system; judgement theorem; knowledge discovery; knowledge representation; maximum distribution reduction; rough sets; Approximation methods; Data mining; Educational institutions; Gold; Information systems; Rough sets; Distribution reduction; Interval information systems; Maximum distribution reduction; Rough sets;
Conference_Titel :
Computational Intelligence and Security (CIS), 2013 9th International Conference on
Conference_Location :
Leshan
Print_ISBN :
978-1-4799-2548-3
DOI :
10.1109/CIS.2013.83
