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Communication Dans Un Congrès Année : 2009

Mining top-k periodic-frequent pattern from transactional databases without support threshold

Résumé

Temporal periodicity of patterns can be regarded as an important criterion for measuring the interestingness of frequent patterns in several applications. A frequent pattern can be said periodic-frequent if it appears at a regular interval. In this paper, we introduce the problem of mining the top-k periodic frequent patterns i.e. the periodic patterns with the k highest support. An efficient single-pass algorithm using a best-first search strategy without support threshold, called MTKPP (Mining Top-K Periodic-frequent Patterns), is proposed. Our experiments show that our proposal is efficient.
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Dates et versions

hal-00473910 , version 1 (16-04-2010)

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  • HAL Id : hal-00473910 , version 1

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Komate Amphawan, Philippe Lenca, Athasit Surarerks. Mining top-k periodic-frequent pattern from transactional databases without support threshold. The 3rd International Conference on Advances in Information Technology, Dec 2009, Bangkok, Thailand. pp.18 - 29. ⟨hal-00473910⟩
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