DocumentCode :
468298
Title :
A Rule Extraction Method Based on Meta-information
Author :
Su, Jian ; Weng, Wenyong
Author_Institution :
Zhejiang Univ., Hangzhou
Volume :
3
fYear :
2007
fDate :
24-27 Aug. 2007
Firstpage :
102
Lastpage :
106
Abstract :
Rule extraction is an important research area of rough set theory. Many rule extraction methods, such as LEM2, are proposed. However, almost all these methods are on the assumption that they are dealing with a centralized dataset. A costly work of data integration is inevitable for these methods in case of distributed data environment. Meanwhile, meta-information is a compact description of information system or its sub-systems, and the cost of meta-information integration is much less than data integration. Moreover, since the volume of meta-information is much lower than the corresponding original dataset, the cost of operations on the meta-information is comparatively less. In order to take advantage of the meta-information mechanism, a minimal rule set extraction method is proposed in this paper on the basis of meta-information and the complexity of this method is much less than LEM2.
Keywords :
data mining; data structures; distributed databases; rough set theory; LEM2; data integration; data structure; distributed data environment; information system; meta-information integration; minimal rule set extraction method; rough set theory; Cities and towns; Computer applications; Computer networks; Costs; Data mining; Distributed information systems; Educational institutions; Information systems; Internet; Set theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
Type :
conf
DOI :
10.1109/FSKD.2007.116
Filename :
4406210
Link To Document :
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