Mining High Utility Itemsets from Vertical Distributed Databases

The utility based on itemsets mining approach has been discussed widely in recent years. There are many algorithms mining high utility itemsets (HUIs) by pruning candidates based on the estimated utility values, and based on the transaction-weighted utilization values. These algorithms aim to reduce search space. In this paper, we propose a method for HUIs from vertical distributed databases. This method does not integrate local databases in SlaverSites to MasterSite, and scan local database one time. Experiments show the run-time of this method is more efficient than that in the concentration database.