A Haar wavelet-based multi-resolution representation method of time series data

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

Abstract

Similarity search of time series can be efficiently handled through a multi-resolution representation scheme which offers the possibility to use pre-computed distances that are calculated and stored at indexing time and then utilized at query time together with filters in the form of exclusion conditions which speed up the search. In this paper we introduce a new multi-resolution representation and search framework of time series. Compared with our previous multi-resolution methods which use first degree polynomials to reduce the dimensionality of the time series at different resolution levels, the novelty of this work is that it applies Haar wavelets to represent the time series. This representation is particularly adapted to our multi-resolution approach as discrete wavelet transforms have the ability of reflecting the local and global information content at every resolution level thus enhancing the performance of the similarity search algorithm, which is what we have shown in this paper through extensive experiments on different datasets.

Original languageEnglish
Title of host publicationICAART 2015 - 7th International Conference on Agents and Artificial Intelligence, Proceedings
EditorsStephane Loiseau, Joaquim Filipe, Beatrice Duval, Jaap van den Herik
PublisherSciTePress
Pages620-626
Number of pages7
ISBN (Electronic)9789897580741
Publication statusPublished - 1 Jan 2015
Externally publishedYes
Event7th International Conference on Agents and Artificial Intelligence - Lisbon, Portugal
Duration: 10 Jan 201512 Jan 2015
Conference number: 7th
http://www.icaart.org/?y=2015

Publication series

NameICAART 2015 - 7th International Conference on Agents and Artificial Intelligence, Proceedings
Volume2

Conference

Conference7th International Conference on Agents and Artificial Intelligence
Abbreviated titleICAART 2015
CountryPortugal
CityLisbon
Period10/01/1512/01/15
Internet address

Keywords

  • Dimensionality reduction techniques
  • Haar wavelets
  • Multi-resolution
  • Similarity search
  • Time series data mining

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

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  • Cite this

    Fuad, M. M. M. (2015). A Haar wavelet-based multi-resolution representation method of time series data. In S. Loiseau, J. Filipe, B. Duval, & J. van den Herik (Eds.), ICAART 2015 - 7th International Conference on Agents and Artificial Intelligence, Proceedings (pp. 620-626). (ICAART 2015 - 7th International Conference on Agents and Artificial Intelligence, Proceedings; Vol. 2). SciTePress.