关键词: 关键域子空间, 离群分析, 数据探索性分析, 实时算法

Abstract: Detecting and analyzing outliers are of great importance in many applications，including telecom fraud detection，disease diagnosis，and network invasion detection，etc.Moreover，many of these fields require good real-time performance.The key attribute subspace of outliers is helpfull to find out the extended knowledge of identified outliers，such as their origin and features.Having discussed the relation of outlying individual and its outlying attribute values，this paper proposes a real-time searching algorithm for key attribute subspace of outliers based on data exploration analysis mode.Experimental results show that the approach is scalable and it can efficiently satisfy the demand of real-time outlier analysis.

Key words: key attribute subspace, outlier analysis, data exploration analysis, real-time algorithm