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Threshold Similarity Queries in Large Time Series Databases
Atlanta, Georgia April 03-April 07
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDE.2006.16022nd International Conference on Data ...
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Johannes A?falg, University of Munich
Hans-Peter Kriegel, University of Munich
Peer Kroger, University of Munich
Peter Kunath, University of Munich
Alexey Pryakhin, University of Munich
Matthias Renz, University of Munich
Similarity search in time series data is an active area of research. In this paper, we introduce the novel concept of threshold-similarity queries in time series databases which report those time series exceeding a user-defined query threshold at similar time frames compared to the query time series. In addition, we present a new data structure to support threshold similarity queries efficiently. The performance of our solution is demonstrated by an extensive experimental evaluation.
Citation:
Johannes A?falg, Hans-Peter Kriegel, Peer Kroger, Peter Kunath, Alexey Pryakhin, Matthias Renz, "Threshold Similarity Queries in Large Time Series Databases," icde, pp.149, 22nd International Conference on Data Engineering (ICDE'06), 2006
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