Threshold Similarity Queries in Large Time Series Databases

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	Similar Articles Articles by Johannes A?falg Articles by Hans-Peter Kriegel Articles by Peer Kroger Articles by Peter Kunath Articles by Alexey Pryakhin Articles by Matthias Renz

22nd International Conference on Data Engineering (ICDE'06)

Atlanta, Georgia

April 03-April 07

ISBN: 0-7695-2570-9

	ASCII Text	x
	Johannes A?falg, Hans-Peter Kriegel, Peer Kroger, Peter Kunath, Alexey Pryakhin, Matthias Renz, "Threshold Similarity Queries in Large Time Series Databases," Data Engineering, International Conference on, pp. 149, 22nd International Conference on Data Engineering (ICDE'06), 2006.

	BibTex	x
	@article{ 10.1109/ICDE.2006.160, author = {Johannes A?falg and Hans-Peter Kriegel and Peer Kroger and Peter Kunath and Alexey Pryakhin and Matthias Renz}, title = {Threshold Similarity Queries in Large Time Series Databases}, journal ={Data Engineering, International Conference on}, volume = {0}, year = {2006}, isbn = {0-7695-2570-9}, pages = {149}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDE.2006.160}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Engineering, International Conference on TI - Threshold Similarity Queries in Large Time Series Databases SN - 0-7695-2570-9 SP EP A1 - Johannes A?falg, A1 - Hans-Peter Kriegel, A1 - Peer Kroger, A1 - Peter Kunath, A1 - Alexey Pryakhin, A1 - Matthias Renz, PY - 2006 KW - null VL - 0 JA - Data Engineering, International Conference on ER -

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

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDE.2006.160

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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