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
Country/TerritoryDenmark
CityAalborg
Period08/07/200910/07/2009
SeriesLecture Notes in Computer Science
Volume5644
ISSN0302-9743

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