DocumentCode :
475922
Title :
Knowledge reduction based on incremental algorithms on attribute space
Author :
Li, Dao-guo ; Xia, Fu-chun ; Liu, Da-wei
Author_Institution :
Inst. of Manage. Sci. & Inf. Eng., Hangzhou Dianzi Univ., Hangzhou
Volume :
1
fYear :
2008
fDate :
12-15 July 2008
Firstpage :
262
Lastpage :
267
Abstract :
Information System is a kind of important form of knowledge representation system, and most of the existing incremental algorithm investigators focus on adding objects to IS. In this paper, the change laws of the core and the reductions with increasing any attributes to a information system are discussed based on the concepts defined, then the a single attribute incremental algorithm and the many attributes incremental algorithm are presented. The examples show that the efficiency of computing of the core and the reductions of the extension information system based on the incremental algorithms may be improved.
Keywords :
knowledge representation; rough set theory; attribute space; information system; knowledge reduction; knowledge representation system; single attribute incremental algorithm; Conference management; Cybernetics; Information management; Information systems; Knowledge management; Machine learning; Machine learning algorithms; Rough sets; Space technology; Technology management; Attribute Reduction; Incremental Algorithm; Information System; Restrained relative positive region; Rough Sets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
Type :
conf
DOI :
10.1109/ICMLC.2008.4620415
Filename :
4620415
Link To Document :
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