A Survey on Different Approaches for Sequential Pattern Mining

Abstract

In data mining, mining sequential pattern from very huge amount of database is very useful in many applications. Most of sequential pattern mining algorithms work on static data means the database should not change. But the databases in today’s real world application do not have static data, they are incremental databases. New transactions are added at some intervals of time. For updated database, the algorithm needs to be executed again for whole sequence database. So those approaches are not appropriate to use, for that algorithm with incremental approach should be modelled and used. This paper analysis existing approaches for finding sequential pattern mining, and the survey would be helpful in forming a new model or improving some existing approach to handle incremented database & obtain sequential patterns out of them.