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
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;
Conference_Titel :
Signal Processing, 2002 6th International Conference on
Print_ISBN :
0-7803-7488-6
DOI :
10.1109/ICOSP.2002.1180006
