Affiliations: Department of Mathematics, Bohai university, Jinzhou, 121000, P.R. China. [email protected] | Department of Mathematics and Physics, North China Electric Power University, Beijing 102206, P. R. China | Department of Mathematics and Computer Science, Hebei University, Baoding, 071002, PR China | School of Computer Science and Technology, Tianjin University, Tianjin 300072, P.R. China
Note: [] Funding was provided in part by the National Natural Science Foundation of China under Grant No. 61070242 and the Program for Liaoning Excellent Talents in University under Grant (LR2012039). Address for correspondence: Department of Mathematics, Bohai university, Jinzhou, 121000, P.R.China.
Note: [] Funding was provided in part by the National Natural Science Foundation of China under Grant No.71171080.
Note: [] Funding was provided inpart by the natural science foundation of Hebei Province (F2012201023), Shenzhen Key Laboratory for High Performance Data Mining with Shenzhen New Industry Development Fund under grant No.CXB201005250021A, and Scientific Research Project of Hebei University (09265631D-2).
Note: [] Funding was provided in part by the National Natural Science Foundation of China under Grant No.10978011.
Abstract: Covering information systems and ordered information systems are two important types of information systems. In this paper the relationships between covering information systems and ordered information systems are first examined, and it is proved that these two types of information systems are isomorphic under given conditions and can be equivalently transformed into each other. Then, the approach to attribute reduction in ordered information systems is proposed. Based on the isomorphism and equivalence of transformation, the method of attribute reduction in a covering information system can be directly obtained according to the reduction approach in an ordered information system. A practical example is employed to show that the proposed method is an effective technique to deal with complex data sets.
Keywords: Information systems, coverings, dominance relations, rough sets, attribute reduction
