Mining long frequent sequences that contain a combinatorial number of frequent subsequences or using very low support thresholds to mine sequential patterns is both time-and memory-consuming. The mining of closed sequential patterns, sequential generator patterns, and maximum sequences has been proposed to overcome this problem. This paper proposes an algorithm for generating all sequential generator patterns. This algorithm uses a vertical approach to listing and counting the support of sequence based on the prime block encoding approach to represent candidate sequences and determine the frequency for each candidate. The search space of the proposed algorithm is much smaller than those of other algorithms because super sequence frequency-based pruning and non-generator-based pruning are applied. Besides, hash tables are also used for fast checking the existed sequential generator patterns. Experimental results conducted on synthetic and real databases show that the proposed algorithm is effective.
['Thi–Thiet Pham', 'Jiawei Luo', 'Tzung Pei Hong']
An efficient algorithm for mining sequential generator pattern using prefix trees and hash tables