Abstract
Data that were appeared in the order of time and stored in a sequence database can be processed to obtain sequential patterns. Sequential pattern mining is the process to obtain sequential patterns from database. However, large amount of data with a variety of data type and rapid data growth raise the scalability issue in data mining process. On the other hand, user needs to analyze data based on specific organizational needs. Therefore, constraint is used to impose limitation in the mining process. Constraint in sequential pattern mining can reduce the short and trivial sequential patterns so that the sequential patterns satisfy user needs. Progressive mining of sequential patterns, PISA, based on single constraint utilizes Period of Interest (POI) as predefined time frame set by user in progressive sequential tree. Single constraint checking in PISA utilizes the concept of anti monotonic or monotonic constraint. Therefore, the number of sequential patterns will decrease, the total execution time of mining process will decrease and as a result, the system scalability will be achieved.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: TELKOMNIKA (Telecommunication Computing Electronics and Control)
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.