EFFICIENTLY MINING CLOSED SEQUENTIAL PATTERNS USING PREFIX TREE

Abstract

Mining closed sequential patterns is one of important tasks in data mining. It is proposed to resolve difficult problems in mining sequential pattern such as mining long frequent sequences that contain a combinatorial number of frequent subsequences or using very low support thresholds to mine sequential patterns is usually both time- and memory-consuming. So, using the parent–child relationship on prefix tree structure to improve the performance of the mining sequential patterns process from the sequence database is also one of important methods in data mining, specially in the mining closed sequential patterns. This paper produces an effective algorithm and experimental results for mining closed sequential patterns from the sequence database using the parent–child relationship on the prefix tree structure. Experimental results show that the performance runtime of the proposed algorithm is much faster than that of other algorithms by more than one order of magnitude and the number of sequential patterns is reduced significantly.