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Resource Abstract:
- Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems,
music and video streams, medical monitoring, and financial systems. Domain experts are often interested in searching for interesting
multivariate patterns from these MTS databases which can contain up to several gigabytes of data. Surprisingly, research on
MTS search is very limited. Most existing work only supports queries with the same length of data, or queries on a fixed set
of variables. In this paper, we propose an efficient and flexible subsequence search framework for massive MTS databases,
that, for the first time, enables querying on any subset of variables with arbitrary time delays between them. We propose
two provably correct algorithms to solve this problem (1) an R-tree Based Search (RBS) which uses Minimum Bounding Rectangles
(MBR) to organize the subsequences, and (2) a List Based Search (LBS) algorithm which uses sorted lists for indexing. We demonstrate
the performance of these algorithms using two large MTS databases from the aviation domain, each containing several millions
of observations. Both these tests show that our algorithms have very high prune rates (>95%) thus needing actual disk access
for only less than 5% of the observations. To the best of our knowledge, this is the first flexible MTS search algorithm capable
of subsequence search on any subset of variables. Moreover, MTS subsequence search has never been attempted on datasets of
the size we have used in this paper.
Citation
- Title Fast and Flexible Multivariate Time Series Subsequence Search
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- revision Date
2014-01-06T11:45:40
Resource language:
[u'en-US']
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point of contact
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publisher
- individual Name {u'hasEmail': u'mailto:ashok.n.srivastava@gmail.com', u'fn': u'Ashok Srivastava'}
- organisation Name
{u'subOrganizationOf': {u'subOrganizationOf': {u'name': u'U.S. Government'}, u'name': u'National Aeronautics and Space Administration'},
u'name': u'Dashlink'}
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Metadata data stamp:
2014-01-06T11:45:40
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publisher
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dataset
Metadata standard for this record:
ISO 19115:2003 - Geographic information - Metadata
standard version:
ISO 19115:2003
Metadata record identifier:
DASHLINK_282
Metadata record format is ISO19139 XML (MD_Metadata)