@inproceedings{2f5005bdd3804c53bb2fc461b9ba6ca3,
title = "Case base maintenance based on outlier data mining",
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 base, Case base maintenance, Case-based reasoning, Data mining, Outlier mining",
author = "Ni, \{Zhi Wei\} and Yu Liu and Li, \{Feng Gang\} and Yang, \{Shan Lin\}",
year = "2005",
language = "英语",
isbn = "078039092X",
series = "2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005",
pages = "2861--2864",
booktitle = "2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005",
note = "International Conference on Machine Learning and Cybernetics, ICMLC 2005 ; Conference date: 18-08-2005 Through 21-08-2005",
}