Mining Periodic Patterns in Sequence Data

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Mining Periodic Patterns in Sequence Data
Abstract. Periodic pattern mining is the problem that regards temporal regularity. There are many emerging applications in periodic pattern mining, including web usage recommendation, weather prediction, computer networks and biological data. In this paper, we propose a Progressive Timelist-Based Verification (PTV) method to the mining of periodic patterns from a sequence of event sets. The parameter min rep, is employed to specify the minimum number of repetitions required for a valid segment of non-disrupted pattern occurrences. We also describe a partitioning approach to handle extra large/long data sequence. The experiments demonstrate good performance and scalability with large frequent patterns.
Kuo-Yu Huang, Chia-Hui Chang
Added 01 Jul 2010
Updated 01 Jul 2010
Type Conference
Year 2004
Authors Kuo-Yu Huang, Chia-Hui Chang
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