Efficient discovery of frequent continuities by projected window list technology

Kuo Yu Huang, Chia Hui Chang, Kuo Zui Lin

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


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.

Original languageEnglish
Pages (from-to)1041-1064
Number of pages24
JournalJournal of Information Science and Engineering
Issue number4
StatePublished - Jul 2008


  • Candidate-free enumeration
  • Data mining
  • Frequent continuity
  • Inter-transaction pattern
  • Pattern growth


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