ClosedPROWL: Efficient mining of closed frequent continuities by projected window list technology

Kuo Yu Huang, Chia Hui Chang, Kuo Zui Lin

Research output: Contribution to conferencePaperpeer-review

5 Scopus citations

Abstract

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.

Original languageEnglish
Pages501-505
Number of pages5
DOIs
StatePublished - 2005
Event5th SIAM International Conference on Data Mining, SDM 2005 - Newport Beach, CA, United States
Duration: 21 Apr 200523 Apr 2005

Conference

Conference5th SIAM International Conference on Data Mining, SDM 2005
Country/TerritoryUnited States
CityNewport Beach, CA
Period21/04/0523/04/05

Keywords

  • Association rules
  • Mining methods and algorithms
  • Temporal databases

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