Article ID Journal Published Year Pages File Type
553804 Decision Support Systems 2010 11 Pages PDF
Abstract

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.

Related Topics
Physical Sciences and Engineering Computer Science Information Systems
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