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- Title
Discovery of Periodic Patterns in Sequence Data: A Variance-Based Approach.
- Authors
Yang, Yinghui (Catherine); Padmanabhan, Balaji; Hongyan Liu; Xiaoyu Wang
- Abstract
We address the discovery of periodic patterns in sequence data. Building on prior work in this area, we W present definitions and new methods for characterizing and identifying four types of periodic patterns. A unifying concept across the different types of periodic patterns we consider is the use of statistical variance to define periodicity. This lends itself to efficient variance-reduction algorithms for identifying periodic patterns. We motivate and test our approach using both extensive simulated sequences and real sequence data from online clickstream data.
- Subjects
SEQUENTIAL pattern mining; VARIANCES; DATA mining; SIMULATION methods &; models; MATHEMATICAL sequences; COMPUTER algorithms; MATHEMATICAL analysis
- Publication
INFORMS Journal on Computing, 2012, Vol 24, Issue 3, p372
- ISSN
1091-9856
- Publication type
Article
- DOI
10.1287/ijoc.1110.0457