Incremental Discovery of Sequential Patterns

In this paper incremental discovery of sequential patterns from a large sequence database is studied A sequential pattern has the form where and are subsequences in the database which says that events will be followed by events with some minimum support and con dence We consider the scenario that sequential patterns have previously been discovered and materialized and an update is subsequently made to the database Rediscovering all patterns by scanning the whole database is not acceptable in a dynamic and large database environment We propose an incremental discovery algorithm that produces the updated patterns by scanning only the a ected part of the database and data structures In addition the algorithm handles the dynamism of the minimum support and con dence without recomputation allowing the user to tune these parameters and focus on most interesting patterns at little overhead Experiments and comparisons were conducted to test the e ectiveness of the proposed algorithm