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Permanent link (DOI): https://doi.org/10.7939/R3QB9VD99

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Time Series Discords Open Access

Descriptions

Other title
Subject/Keyword
Anomaly Detection
Discord
Time Series
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Mueller, David A.
Supervisor and department
Sander, Joerg (Computing Science)
Parsons, Ian (Computing Science)
Examining committee member and department
Parsons, Ian (Computing Science)
Sander, Joerg (Computing Science)
Rafiei, Davood (Computing Science)
Department
Department of Computing Science
Specialization

Date accepted
2013-09-26T14:39:00Z
Graduation date
2013-11
Degree
Master of Science
Degree level
Master's
Abstract
Time series discords, as introduced in by Keogh et al. [5] is described as the subsequence in the time series which is maximally different from the rest of the subsequences. Discovery of time series discords has been applied to several diverse domains including space shuttle telemetry, industry, and medicine [5] to detect anomalies in the data which can identify equipment failure, unusual patterns of activity and health problems. In this thesis we will examine the problem of finding time series discords, with detailed analysis of the problem and analysis of the effectiveness of prior work. Three different areas of discord discovery will be examined: Top Discord, Variable Length Discords, and Top-K Discords. In each of these areas, we strive to reduce the number or ease the selection of input parameters required by the end user. Emphasis is also placed on improved runtime and scalability of discord discovery methods.
Language
English
DOI
doi:10.7939/R3QB9VD99
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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