ELKI in time: ELKI 0.2 for the performance evaluation of distance measures for time series

Elke Achtert*, Thomas Bernecker, Hans Peter Kriegel, Erich Schubert, Arthur Zimek

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

ELKI is a unified software framework, designed as a tool suitable for evaluation of different algorithms on high dimensional real-valued feature-vectors. A special case of high dimensional real-valued feature-vectors are time series data where traditional distance measures like L p -distances can be applied. However, also a broad range of specialized distance measures like, e.g., dynamic time-warping, or generalized distance measures like second order distances, e.g., shared-nearest-neighbor distances, have been proposed. The new version ELKI 0.2 now is extended to time series data and offers a selection of these distance measures. It can serve as a visualization- and evaluation-tool for the behavior of different distance measures on time series data.

Original languageEnglish
Title of host publicationAdvances in Spatial and Temporal Databases - 11th International Symposium, SSTD 2009, Proceedings
EditorsN. Mamoulis, T. Seidl, T. B. Pedersen, K. Torp, I. Assent
PublisherSpringer
Publication date2. Nov 2009
Pages436-440
ISBN (Print)978-3-642-02981-3
ISBN (Electronic)978-3-642-02982-0
DOIs
Publication statusPublished - 2. Nov 2009
Externally publishedYes
Event11th International Symposium on Spatial and Temporal Databases - Aalborg, Denmark
Duration: 8. Jul 200910. Jul 2009

Conference

Conference11th International Symposium on Spatial and Temporal Databases
CountryDenmark
CityAalborg
Period08/07/200910/07/2009
SeriesLecture Notes in Computer Science
Volume5644
ISSN0302-9743

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Achtert, E., Bernecker, T., Kriegel, H. P., Schubert, E., & Zimek, A. (2009). ELKI in time: ELKI 0.2 for the performance evaluation of distance measures for time series. In N. Mamoulis, T. Seidl, T. B. Pedersen, K. Torp, & I. Assent (Eds.), Advances in Spatial and Temporal Databases - 11th International Symposium, SSTD 2009, Proceedings (pp. 436-440). Springer. Lecture Notes in Computer Science, Vol.. 5644 https://doi.org/10.1007/978-3-642-02982-0_35
Achtert, Elke ; Bernecker, Thomas ; Kriegel, Hans Peter ; Schubert, Erich ; Zimek, Arthur. / ELKI in time : ELKI 0.2 for the performance evaluation of distance measures for time series. Advances in Spatial and Temporal Databases - 11th International Symposium, SSTD 2009, Proceedings. editor / N. Mamoulis ; T. Seidl ; T. B. Pedersen ; K. Torp ; I. Assent. Springer, 2009. pp. 436-440 (Lecture Notes in Computer Science, Vol. 5644).
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abstract = "ELKI is a unified software framework, designed as a tool suitable for evaluation of different algorithms on high dimensional real-valued feature-vectors. A special case of high dimensional real-valued feature-vectors are time series data where traditional distance measures like L p -distances can be applied. However, also a broad range of specialized distance measures like, e.g., dynamic time-warping, or generalized distance measures like second order distances, e.g., shared-nearest-neighbor distances, have been proposed. The new version ELKI 0.2 now is extended to time series data and offers a selection of these distance measures. It can serve as a visualization- and evaluation-tool for the behavior of different distance measures on time series data.",
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Achtert, E, Bernecker, T, Kriegel, HP, Schubert, E & Zimek, A 2009, ELKI in time: ELKI 0.2 for the performance evaluation of distance measures for time series. in N Mamoulis, T Seidl, TB Pedersen, K Torp & I Assent (eds), Advances in Spatial and Temporal Databases - 11th International Symposium, SSTD 2009, Proceedings. Springer, Lecture Notes in Computer Science, vol. 5644, pp. 436-440, 11th International Symposium on Spatial and Temporal Databases, Aalborg, Denmark, 08/07/2009. https://doi.org/10.1007/978-3-642-02982-0_35

ELKI in time : ELKI 0.2 for the performance evaluation of distance measures for time series. / Achtert, Elke; Bernecker, Thomas; Kriegel, Hans Peter; Schubert, Erich; Zimek, Arthur.

Advances in Spatial and Temporal Databases - 11th International Symposium, SSTD 2009, Proceedings. ed. / N. Mamoulis; T. Seidl; T. B. Pedersen; K. Torp; I. Assent. Springer, 2009. p. 436-440 (Lecture Notes in Computer Science, Vol. 5644).

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Achtert E, Bernecker T, Kriegel HP, Schubert E, Zimek A. ELKI in time: ELKI 0.2 for the performance evaluation of distance measures for time series. In Mamoulis N, Seidl T, Pedersen TB, Torp K, Assent I, editors, Advances in Spatial and Temporal Databases - 11th International Symposium, SSTD 2009, Proceedings. Springer. 2009. p. 436-440. (Lecture Notes in Computer Science, Vol. 5644). https://doi.org/10.1007/978-3-642-02982-0_35