Distributed Algorithms to Find Similar Time Series

Oleksandra Levchenko, Boyan Kolev, Djamel Edine Yagoubi, Dennis Shasha, Themis Palpanas, Patrick Valduriez, Reza Akbarinia, Florent Masseglia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As sensors improve in both bandwidth and quantity over time, the need for high performance sensor fusion increases. This requires both better (quasi-linear time if possible) algorithms and parallelism. This demonstration uses financial and seismic data to show how two state-of-the-art algorithms construct indexes and answer similarity queries using Spark. Demo visitors will be able to choose query time series, see how each algorithm approximates nearest neighbors and compare times in a parallel environment.

Original languageEnglish (US)
Title of host publicationMachine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Proceedings
EditorsUlf Brefeld, Elisa Fromont, Andreas Hotho, Arno Knobbe, Marloes Maathuis, Céline Robardet
PublisherSpringer
Pages781-785
Number of pages5
ISBN (Print)9783030461324
DOIs
StatePublished - 2020
EventEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2019 - Wurzburg, Germany
Duration: Sep 16 2019Sep 20 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11908 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2019
CountryGermany
CityWurzburg
Period9/16/199/20/19

Keywords

  • Distributed data processing
  • Indexing
  • Similarity search
  • Spark
  • Time series

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Levchenko, O., Kolev, B., Yagoubi, D. E., Shasha, D., Palpanas, T., Valduriez, P., Akbarinia, R., & Masseglia, F. (2020). Distributed Algorithms to Find Similar Time Series. In U. Brefeld, E. Fromont, A. Hotho, A. Knobbe, M. Maathuis, & C. Robardet (Eds.), Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2019, Proceedings (pp. 781-785). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11908 LNAI). Springer. https://doi.org/10.1007/978-3-030-46133-1_51