Discovering sub-patterns from time series using a normalized cross-match algorithm
Xueyuan Gong1; Simon Fong1; Raymond K. Wong2; Sabah Mohammed3; Jinan Fiaidhi3; Athanasios V. Vasilakos4
Source PublicationJournal of Supercomputing

Time series data stream mining has attracted considerable research interest in recent years. Pattern discovery is a challenging problem in time series data stream mining. Because the data update continuously and the sampling rates may be different, dynamic time warping (DTW)-based approaches are used to solve the pattern discovery problem in time series data streams. However, the naive form of the DTW-based approach is computationally expensive. Therefore, Toyoda proposed the CrossMatch (CM) approach to discover the patterns between two time series data streams (sequences), which requires only O(n) time per data update, where n is the length of one sequence. CM, however, does not support normalization, which is required for some kinds of sequences (e.g. stock prices, ECG data). Therefore, we propose a normalized-CrossMatch approach that extends CM to enforce normalization while maintaining the same performance capabilities.

KeywordCrossmatch Data Streams Ncm Pattern Discovery Time Series
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Indexed BySCI
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000385417400010
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Document TypeJournal article
Corresponding AuthorXueyuan Gong; Simon Fong; Raymond K. Wong; Sabah Mohammed; Jinan Fiaidhi; Athanasios V. Vasilakos
Affiliation1.Department of Computer and Information Science, University of Macau, Macau, China
2.School of Computer Science and Engineering, University of New South Wales, Sydney, Australia
3.Department of Computer Science, Lakehead University, Thunder Bay, Canada
4.Department of Computer Science, Electrical and Space Engineering, Lulea University of Technology, Lulea, Sweden
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
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GB/T 7714
Xueyuan Gong,Simon Fong,Raymond K. Wong,et al. Discovering sub-patterns from time series using a normalized cross-match algorithm[J]. Journal of Supercomputing,2016,72(10):3850-3867.
APA Xueyuan Gong,Simon Fong,Raymond K. Wong,Sabah Mohammed,Jinan Fiaidhi,&Athanasios V. Vasilakos.(2016).Discovering sub-patterns from time series using a normalized cross-match algorithm.Journal of Supercomputing,72(10),3850-3867.
MLA Xueyuan Gong,et al."Discovering sub-patterns from time series using a normalized cross-match algorithm".Journal of Supercomputing 72.10(2016):3850-3867.
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