An Incremental Updating Sequential Pattern Mining Algorithm Based on Weight Function

To effectively update the rules when some new data are added,this paper proposes an incremental updating sequential pattern mining algorithm based on weight functions-UWIUA(updated weight incremental updating algorithm).The algorithm can delete the subsequential sets using the weight and generate new candidate sequential sets using the infrequent sequential sets in the knowledge database.It needn't visit the old database again and again,so it can avoid the problem that candidate sequential sets are very large,and can decrease the run time and memory spaces.It improves the algorithm performance greatly.The experimental results show that UWIUA is more efficient than IUA(incremental updating algorithm).