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Case base maintenance based on outlier data mining

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.