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Normalized Cross-Match: Pattern Discovery Algorithm from Biofeedback Signals
Xueyuan Gong2; Simon Fong2; Yain-Whar Si2; Robert P. Biuk-Aghai2; Raymond K. Wong3; Athanasios V. Vasilakos1
2016
Conference Name20th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)
Source PublicationTRENDS AND APPLICATIONS IN KNOWLEDGE DISCOVERY AND DATA MINING (PAKDD 2016)
Volume9794
Pages169-180
Conference DateApril 19, 2016
Conference PlaceAuckland, New Zealand
PublisherSPRINGER INT PUBLISHING AG, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
Abstract

Biofeedback signals are important elements in critical care applications, such as monitoring ECG data of a patient, discovering patterns from large amount of ECG data sets, detecting outliers from ECG data, etc. Because the signal data update continuously and the sampling rates may be different, time-series data stream is harder to be dealt with compared to traditional historical time-series data. For the pattern discovery problem on time-series streams, Toyoda proposed the CrossMatch (CM) approach to discover the patterns between two timeseries 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. EEG data, ECG data). Therefore, we propose a normalized-CrossMatch approach (NCM) that extends CM to enforce normalization while maintaining the same performance capabilities.

KeywordCrossmatch Ncm Pattern Discovery Time-series Streams
DOIhttps://doi.org/10.1007/978-3-319-42996-0_14
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications
WOS IDWOS:000386511900014
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Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Department of Computer Science, Electrical and Space Engineering, Lulea University of Technology, Lulea, Sweden
2.Department of Computer and Information Science, University of Macau, Macau, China
3.School of Computer Science and Engineering, University of New South Wales, Sydney, Australia
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Xueyuan Gong,Simon Fong,Yain-Whar Si,et al. Normalized Cross-Match: Pattern Discovery Algorithm from Biofeedback Signals[C]:SPRINGER INT PUBLISHING AG, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND,2016:169-180.
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