Maintenance of Pre-large FUSP Trees in Dynamic Databases

Abstract

In the past, pre-large fast-updated sequential pattern trees (pre-large FUSP tree) were proposed for efficiently mining large sequences for record insertion and deletion, respectively. In this paper, we thus proposed a maintenance approach for efficiently maintaining pre-large FUSP trees and effectively deriving desired large sequences when data in databases are modified. Experimental results also show that the proposed algorithm has a better performance in execution time.