Abstract: This paper proposes a novel algorithm MFSPAN (maximal frequent sequential pattern mining algorithm). MFSPAN is used to mine the com plete set of maximal frequent sequential patterns in sequence databases. It solves the problem that the number of frequent subsequences will increase explosively as frequent patterns become longer: because MFSPAN takes full advantage of the property that different sequences may share a common prefix to reduce itemset comparing times. Experiments on standard test data show that MFSPAN is very effective.

Key words: sequential pattern, maximal sequential pattern, long pattern, depthfirst