EfficientDiscovery of Frequent Continuities by Projected Window List Technology

摘要

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 withexact position between the records. Since continuities break the boundaries of records, the number ofpotential patterns will increase drastically. An alternative approach is to mine compressed or closedfrequent continuities. Mining compressed/closed frequent patterns has the same power as mining thecomplete 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(PWL) technology for the mining of frequent continuities. We present a series of frequent continuitymining algorithms, including PROWL+, COCOA and ClosedPROWL. Experimental evaluation on bothreal world and synthetic datasets shows that our algorithm is more efficient than previously proposedalgorithms.