Generalization of RST in ordered information table

This paper studies one newly-emerging area of data mining-ordered information table. This paper uses rough set theory to mine rules in ordered information table. Compared with traditional rough set theory based methods, applications in ordered information table deal with ordering objects instead of classifying them, in which objects are ordered both by descriptive and overall attributes, and rules to be mined are actually the association between them. In order to mine rules of such form, this paper generalizes rough set theory under the core relation in ordered information table partial order. Subsequent experiments show that efficiency of the method in this paper is higher than that of previous approaches.