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Mining frequent patterns is a fundamental 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 compressed or closed frequent continuities (CFC). Mining CFCs 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 (PWL) technology for the mining of frequent continuities. We present a series of frequent continuity mining algorithms, including PROWL+, COCOA and ClosedPROWL. Experimental evaluation shows that our algorithm is more efficient than previously works.

Keywords: data mining, frequent continuity, inter-transaction pattern, pattern growth, candidate-free enumeration

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Received July 24, 2006; revised July 17, 2007; accepted September 5, 2007.
Communicated by Chung-Sheng Li.
^*This work was sponsored by the National Science Council of Taiwan, R.O.C. under grant No. NSC 95-2524- S-008-001.