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
2016-10-01
Source PublicationJournal of Supercomputing
ISSN0920-8542
Volume72Issue:10Pages:3850-3867
Abstract

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
DOIhttps://doi.org/10.1007/s11227-016-1632-z
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS IDWOS:000385417400010
PublisherSPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
Fulltext Access
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
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
Recommended Citation
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.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Xueyuan Gong]'s Articles
[Simon Fong]'s Articles
[Raymond K. Wong]'s Articles
Baidu academic
Similar articles in Baidu academic
[Xueyuan Gong]'s Articles
[Simon Fong]'s Articles
[Raymond K. Wong]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Xueyuan Gong]'s Articles
[Simon Fong]'s Articles
[Raymond K. Wong]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.