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Efficient Algorithm for Mining Temporal Association Rule


Junheng-Huang, Wang-Wei


Vol. 7  No. 4  pp. 268-271


It presents an SPFA(Standing for Segmented Progressive Filter Algorithm).The basic idea behind SPFA is to first segment the database into sub-databases in such a way that item in each sub-database will have either the common starting time or the common ending time. Then, for each sub-databse, SPFA progressively filters candidate 2-itemsets with cumulative filtering thresholds either forward or backward in time. This feature allows SPFA of adopting the scan reduction technique by generating all candidate k-itemsets from candidate 2-itemsets directly. The experimental results show that SPFA significantly outperforms other schemes which are extended from prior methods in terms of the execution time and scalability. The advantage of SPFA becomes even more prominent as the size of the database increases.


Association rule; Itemset; Data mining