关键词: 粒计算, 粗糙集, 异常数据挖掘, 知识粒度

Abstract: Granular computing theory is a new efficient method to deal with uncertain, incomplete and inconsistent knowledge. Knowledge granulation is one of important tools to deal with uncertain information in granular computing theory. Many existing algorithms of outlier mining mainly aim for certain data, very little work has been done for uncertain data aiming to outlier mining based on knowledge granulation. Therefore, after introducing knowledge granulation concept, relative knowledge granulation and outlier degree are defined for measuring the outlier data. A new algorithm for outlier mining based on knowledge granulation is proposed. This algorithm can effectively obtain outliers from data set. The validity of the algorithm is depicted by an example.

Key words: granular computing, rough sets, outlier data mining, knowledge granulation