International Journal of Soft Computing and Engineering (IJSCE)
Extensive growth of data gives the motivation to find meaningful patterns among the huge data. Sequential pattern provides the users' interesting relationships between different items in sequential database. In the real world, there are several applications in which specific sequences are more important than other sequences. Traditional Sequential pattern approaches are suffering from two disadvantages: all the items and sequences are treated uniformly. Conventional algorithms are generating large number of patterns for lower support. In addition, the unimportant patterns with low weights can be detected.