Title :
Case base maintenance based on outlier data mining
Author :
Ni, Zhi-wei ; Liu, Yu ; Li, Feng-gang ; Yang, Shan-Lin
Author_Institution :
Inst. of Comput. Network Syst., Hefei Univ. of Technol., China
Abstract :
In case-based reasoning (CBR) system, as the scale of case base is enlarging, the system performance is gradually dropping. This paper mainly discusses how to maintain case bases in CBR system by adopting outlier data mining and case sieving techniques. Experimental results have shown that the proposed algorithm can maintain case bases satisfactorily and stably, thus assuring the good performance of CBR system.
Keywords :
case-based reasoning; data mining; case base maintenance; case sieving; case-based reasoning; outlier data mining; Computer aided software engineering; Computer networks; Data mining; Electronic mail; History; Humans; Information filtering; Large-scale systems; Problem-solving; System performance; Case base; Case base maintenance; Case-based reasoning; Outlier mining; data mining;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527430
