DocumentCode
3180548
Title
The interestingness and robustness of knowledge in incremental data mining
Author
Lihong, Wang ; Bofeng, Zhang ; Gengfeng, W.U.
Author_Institution
Sch. of Comput. Eng. & Technol., Shanghai Univ., China
Volume
2
fYear
2002
fDate
26-30 Aug. 2002
Firstpage
1203
Abstract
This paper represents the knowledge with timing rules in incremental data mining, focusing on the interest and robustness of knowledge. We can find the interesting knowledge from the conflict between history rules and current rules and the robust knowledge by computing the belief degree of history rules on the new data set.
Keywords
data mining; database management systems; database theory; belief degree; history rules; incremental data mining; knowledge interest; knowledge robustness; timing rules; Data engineering; Data mining; Database systems; Degradation; History; Knowledge engineering; Parallel processing; Robustness; Timing;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, 2002 6th International Conference on
Print_ISBN
0-7803-7488-6
Type
conf
DOI
10.1109/ICOSP.2002.1180006
Filename
1180006
Link To Document