New approach for the sequential pattern mining of high-dimensional sequence databases

作者：Liu Hongyan^*; Lin Fangzhou; He Jun; Cai Yunjue

来源：Decision Support Systems, 2010, 50(1): 270-280.

DOI：10.1016/j.dss.2010.08.029

• Sequential pattern mining
• High-dimensional database
• Data mining

In this paper a new algorithm, the Top-Down mining of Sequential patterns (TD-Seq), for mining sequential patterns from high-dimensional stock sequence databases is presented. Existing algorithms are limited by efficiency problems in dealing with high-dimensional sequence databases. To address this problem, a two-phase mining method is proposed, in which a top-down transposition-based searching strategy as well as a new support counting method are exploited. Three pruning rules were also developed to reduce the search space further. Experiments conducted on actual databases demonstrate the improved performance of TD-Seq over existing algorithms.

• 出版日期2010-12
• 单位清华大学