DocumentCode
3448299
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
fYear
1996
fDate
11-14 Dec 1996
Firstpage
152
Lastpage
157
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/AFSS.1996.583581
Filename
583581
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