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IDEAL
2003
Springer

Improving the Efficiency of Frequent Pattern Mining by Compact Data Structure Design

14 years 4 months ago
Improving the Efficiency of Frequent Pattern Mining by Compact Data Structure Design
Mining frequent patterns has been a topic of active research because it is computationally the most expensive step in association rule discovery. In this paper, we discuss the use of compact data structure design for improving the efficiency of frequent pattern mining. It is based on our work in developing efficient algorithms that outperform the best available frequent pattern algorithms on a number of typical data sets. We discuss improvements to the data structure design that has resulted in faster frequent pattern discovery. The performance of our algorithms is studied by comparing their running times on typical test data sets against the fastest Apriori, Eclat, FP-Growth and OpportuneProject algorithms. We discuss the performance results as well as the strengths and limitations of our algorithms.
Raj P. Gopalan, Yudho Giri Sucahyo
Added 07 Jul 2010
Updated 07 Jul 2010
Type Conference
Year 2003
Where IDEAL
Authors Raj P. Gopalan, Yudho Giri Sucahyo
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