ClosedPROWL: Efficient Mining of Closed Frequent Continuities by Projected Window List Technology

Mining frequent patterns in databases is a fundamental and essential problem in data mining research. A continuity is a kind of causal relationship which describes a definite temporal factor with exact position between the records. Since continuities break the boundaries of records, the number of potential patterns will increase drastically. An alternative approach is to mine closed frequent continuities. Mining closed frequent patterns has the same power as mining the complete set of frequent patterns, while substantially reducing redundant rules to be generated and increasing the effectiveness of mining. In this paper, we propose a method called projected window list technology for the mining of frequent continuities. We present a closed frequent continuity mining algorithm, ClosedPROWL. Experimental result shows that our algorithm is more efficient than previously proposed algorithms. Temporal databases, association rules, Mining methods and algorithms