Title :
Models for first order rough logic applications to data mining
Author :
Lin, T.Y. ; Liu, Qing ; Zuo, Xiaoling
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA
Abstract :
Pawlak´s rough set theory has inspired many logical investigations. In their joint paper, T.Y. Lin and Q. Liu have introduced first order rough logic based on their axiomatic characterization of rough sets. In this paper, rough model are fine tuned. Two rough models an defined. Based on new rough models, completeness of rough logic system is indicated for each respective model. Pawlak information system is viewed as rough model, and data mining is formulated in terms of first order rough logic
Keywords :
fuzzy set theory; inference mechanisms; knowledge acquisition; Pawlak information system; Pawlak´s rough set theory; axiomatic characterization; data mining; first order rough logic applications; rough logic; Application software; Computer science; Data engineering; Data mining; Information systems; Logic; Rough sets; Set theory;
Conference_Titel :
Fuzzy Systems Symposium, 1996. Soft Computing in Intelligent Systems and Information Processing., Proceedings of the 1996 Asian
Conference_Location :
Kenting
Print_ISBN :
0-7803-3687-9
DOI :
10.1109/AFSS.1996.583581