Normalized Cross-Match: Pattern Discovery Algorithm from Biofeedback Signals | |
Xueyuan Gong2; Simon Fong2![]() ![]() | |
2016 | |
Conference Name | 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) |
Source Publication | TRENDS AND APPLICATIONS IN KNOWLEDGE DISCOVERY AND DATA MINING (PAKDD 2016) |
Volume | 9794 |
Pages | 169-180 |
Conference Date | April 19, 2016 |
Conference Place | Auckland, New Zealand |
Publisher | SPRINGER 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. |
Keyword | Crossmatch Ncm Pattern Discovery Time-series Streams |
DOI | https://doi.org/10.1007/978-3-319-42996-0_14 |
URL | View the original |
Indexed By | SCI |
Language | 英语 |
WOS Research Area | Computer Science |
WOS Subject | Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications |
WOS ID | WOS:000386511900014 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE |
Affiliation | 1.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 Affilication | University 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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