On the discovery of weak periodicities in large time series

Christos Berberidis; Ioannis Vlahavas; Walid G. Aref; Mikhail Atallah; Ahmed K. Elmagarmid

doi:10.1007/3-540-45681-3_5

On the discovery of weak periodicities in large time series

Christos Berberidis^*, Ioannis Vlahavas, Walid G. Aref, Mikhail Atallah, Ahmed K. Elmagarmid

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

35 Citations (Scopus)

Abstract

The search for weak periodic signals in time series data is an active topic of research. Given the fact that rarely a real world dataset is perfectly periodic, this paper approaches this problem in terms of data mining, trying to discover weak periodic signals in time series databases, when no period length is known in advance. In existing time series mining algorithms, the period length is user-specified. We propose an algorithm for finding approximate periodicities in large time series data, utilizing autocorrelation function and FFT. This algorithm is an extension to the partial periodicity detection algorithm presented in a previous paper of ours. We provide some mathematical background as well as experimental results.

Original language	English
Title of host publication	Principles of Data Mining and Knowledge Discovery - 6th European Conference, PKDD 2002, Proceedings
Editors	Tapio Elomaa, Heikki Mannila, Hannu Toivonen
Publisher	Springer Verlag
Pages	51-61
Number of pages	11
ISBN (Print)	3540440372, 9783540440376
DOIs	https://doi.org/10.1007/3-540-45681-3_5
Publication status	Published - 2002
Externally published	Yes
Event	6th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2002 - Helsinki, Finland Duration: 19 Aug 2002 → 23 Aug 2002

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2431 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2002
Country/Territory	Finland
City	Helsinki
Period	19/08/02 → 23/08/02

Access to Document

10.1007/3-540-45681-3_5

Cite this

Berberidis, C., Vlahavas, I., Aref, W. G., Atallah, M., & Elmagarmid, A. K. (2002). On the discovery of weak periodicities in large time series. In T. Elomaa, H. Mannila, & H. Toivonen (Eds.), Principles of Data Mining and Knowledge Discovery - 6th European Conference, PKDD 2002, Proceedings (pp. 51-61). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2431 LNAI). Springer Verlag. https://doi.org/10.1007/3-540-45681-3_5

Berberidis, Christos ; Vlahavas, Ioannis ; Aref, Walid G. et al. / On the discovery of weak periodicities in large time series. Principles of Data Mining and Knowledge Discovery - 6th European Conference, PKDD 2002, Proceedings. editor / Tapio Elomaa ; Heikki Mannila ; Hannu Toivonen. Springer Verlag, 2002. pp. 51-61 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "On the discovery of weak periodicities in large time series",

abstract = "The search for weak periodic signals in time series data is an active topic of research. Given the fact that rarely a real world dataset is perfectly periodic, this paper approaches this problem in terms of data mining, trying to discover weak periodic signals in time series databases, when no period length is known in advance. In existing time series mining algorithms, the period length is user-specified. We propose an algorithm for finding approximate periodicities in large time series data, utilizing autocorrelation function and FFT. This algorithm is an extension to the partial periodicity detection algorithm presented in a previous paper of ours. We provide some mathematical background as well as experimental results.",

author = "Christos Berberidis and Ioannis Vlahavas and Aref, {Walid G.} and Mikhail Atallah and Elmagarmid, {Ahmed K.}",

year = "2002",

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language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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editor = "Tapio Elomaa and Heikki Mannila and Hannu Toivonen",

booktitle = "Principles of Data Mining and Knowledge Discovery - 6th European Conference, PKDD 2002, Proceedings",

address = "Germany",

note = "6th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2002 ; Conference date: 19-08-2002 Through 23-08-2002",

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Berberidis, C, Vlahavas, I, Aref, WG, Atallah, M & Elmagarmid, AK 2002, On the discovery of weak periodicities in large time series. in T Elomaa, H Mannila & H Toivonen (eds), Principles of Data Mining and Knowledge Discovery - 6th European Conference, PKDD 2002, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2431 LNAI, Springer Verlag, pp. 51-61, 6th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2002, Helsinki, Finland, 19/08/02. https://doi.org/10.1007/3-540-45681-3_5

On the discovery of weak periodicities in large time series. / Berberidis, Christos; Vlahavas, Ioannis; Aref, Walid G. et al.
Principles of Data Mining and Knowledge Discovery - 6th European Conference, PKDD 2002, Proceedings. ed. / Tapio Elomaa; Heikki Mannila; Hannu Toivonen. Springer Verlag, 2002. p. 51-61 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2431 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - On the discovery of weak periodicities in large time series

AU - Berberidis, Christos

AU - Vlahavas, Ioannis

AU - Aref, Walid G.

AU - Atallah, Mikhail

AU - Elmagarmid, Ahmed K.

PY - 2002

Y1 - 2002

N2 - The search for weak periodic signals in time series data is an active topic of research. Given the fact that rarely a real world dataset is perfectly periodic, this paper approaches this problem in terms of data mining, trying to discover weak periodic signals in time series databases, when no period length is known in advance. In existing time series mining algorithms, the period length is user-specified. We propose an algorithm for finding approximate periodicities in large time series data, utilizing autocorrelation function and FFT. This algorithm is an extension to the partial periodicity detection algorithm presented in a previous paper of ours. We provide some mathematical background as well as experimental results.

AB - The search for weak periodic signals in time series data is an active topic of research. Given the fact that rarely a real world dataset is perfectly periodic, this paper approaches this problem in terms of data mining, trying to discover weak periodic signals in time series databases, when no period length is known in advance. In existing time series mining algorithms, the period length is user-specified. We propose an algorithm for finding approximate periodicities in large time series data, utilizing autocorrelation function and FFT. This algorithm is an extension to the partial periodicity detection algorithm presented in a previous paper of ours. We provide some mathematical background as well as experimental results.

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DO - 10.1007/3-540-45681-3_5

M3 - Conference contribution

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SN - 9783540440376

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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PB - Springer Verlag

T2 - 6th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2002

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ER -

Berberidis C, Vlahavas I, Aref WG, Atallah M, Elmagarmid AK. On the discovery of weak periodicities in large time series. In Elomaa T, Mannila H, Toivonen H, editors, Principles of Data Mining and Knowledge Discovery - 6th European Conference, PKDD 2002, Proceedings. Springer Verlag. 2002. p. 51-61. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-45681-3_5

On the discovery of weak periodicities in large time series

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