Article

New Time Series Data Representation ESAX for Financial Applications

Authors:

Battuguldur Lkhagva,

Yu Suzuki,

Kyoji KawagoeAuthors Info & Claims

ICDEW '06: Proceedings of the 22nd International Conference on Data Engineering Workshops

Page 115

https://doi.org/10.1109/ICDEW.2006.99

Published: 03 April 2006 Publication History

Publisher Site

Abstract

Efficient and accurate similarity searching for a large amount of time series data set is an important but non-trivial problem. Many dimensionality reduction techniques have been proposed for effective representation of time series data in order to realize such similarity searching, including Singular Value Decomposition (SVD), the Discrete Fourier transform (DFT), the Adaptive Piecewise Constant Approximation (APCA), and the recently proposed Symbolic Aggregate Approximation (SAX).

Cited By

View all

Hu HQiu JWang HLiang BZou S(2024)DIDS: Double Indices and Double Summarizations for Fast Similarity SearchProceedings of the VLDB Endowment10.14778/3665844.366585117:9(2198-2211)Online publication date: 1-May-2024
https://dl.acm.org/doi/10.14778/3665844.3665851
Marini GGoncalves JVelloso EJurdak RKostakos V(2024)A toolkit for localisation queriesPervasive and Mobile Computing10.1016/j.pmcj.2024.101946103:COnline publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.pmcj.2024.101946
Wang YLyu XYang S(2024)Ocean observing time-series anomaly detection based on DTW-TRSAX methodThe Journal of Supercomputing10.1007/s11227-024-06183-w80:13(18679-18704)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1007/s11227-024-06183-w
Show More Cited By

Index Terms

New Time Series Data Representation ESAX for Financial Applications

Recommendations

Representation of the Fourier Transform by Fourier Series

The analysis of the mathematical structure of the integral Fourier transform shows that the transform can be split and represented by certain sets of frequencies as coefficients of Fourier series of periodic functions in the interval $$[0,2\pi)$$ . In this paper we ...
Fourier transform representation by frequency-time wavelets

A new concept of the A-wavelet transform is introduced, and the representation of the Fourier transform by the A-wavelet transform is described. Such a wavelet transform uses a fully scalable modulated window but not all possible shifts. A geometrical ...
Short-time fractional fourier transform and its applications

The fractional Fourier transform (FRFT) is a potent tool to analyze the chirp signal. However, it fails in locating the fractional Fourier domain (FRFD)-frequency contents which is required in some applications. The short-time fractional Fourier ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

ICDEW '06: Proceedings of the 22nd International Conference on Data Engineering Workshops

April 2006

ISBN:0769525717

Publisher

IEEE Computer Society

United States

Publication History

Published: 03 April 2006

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

13
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 16 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Hu HQiu JWang HLiang BZou S(2024)DIDS: Double Indices and Double Summarizations for Fast Similarity SearchProceedings of the VLDB Endowment10.14778/3665844.366585117:9(2198-2211)Online publication date: 1-May-2024
https://dl.acm.org/doi/10.14778/3665844.3665851
Marini GGoncalves JVelloso EJurdak RKostakos V(2024)A toolkit for localisation queriesPervasive and Mobile Computing10.1016/j.pmcj.2024.101946103:COnline publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.pmcj.2024.101946
Wang YLyu XYang S(2024)Ocean observing time-series anomaly detection based on DTW-TRSAX methodThe Journal of Supercomputing10.1007/s11227-024-06183-w80:13(18679-18704)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1007/s11227-024-06183-w
Criado-Ramón DRuiz LPegalajar M(2022)Electric demand forecasting with neural networks and symbolic time series representationsApplied Soft Computing10.1016/j.asoc.2022.108871122:COnline publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1016/j.asoc.2022.108871
Fathy YBarnaghi PTafazolli R(2018)Large-Scale Indexing, Discovery, and Ranking for the Internet of Things (IoT)ACM Computing Surveys10.1145/315452551:2(1-53)Online publication date: 12-Mar-2018
https://dl.acm.org/doi/10.1145/3154525
Li ZLi ZYu NWen S(2017)Locality-Based Visual Outlier Detection Algorithm for Time SeriesSecurity and Communication Networks10.1155/2017/18697872017Online publication date: 22-Aug-2017
https://dl.acm.org/doi/10.1155/2017/1869787
Zan CYamana HAnderst-Kotsis G(2016)An improved symbolic aggregate approximation distance measure based on its statistical featuresProceedings of the 18th International Conference on Information Integration and Web-based Applications and Services10.1145/3011141.3011146(72-80)Online publication date: 28-Nov-2016
https://dl.acm.org/doi/10.1145/3011141.3011146
Aghabozorgi STeh Y(2014)Stock market co-movement assessment using a three-phase clustering methodExpert Systems with Applications: An International Journal10.1016/j.eswa.2013.08.02841:4(1301-1314)Online publication date: 1-Mar-2014
https://dl.acm.org/doi/10.1016/j.eswa.2013.08.028
Malinowski SGuyet TQuiniou RTavenard R(2013)1d-SAXProceedings of the 12th International Symposium on Advances in Intelligent Data Analysis XII - Volume 820710.1007/978-3-642-41398-8_24(273-284)Online publication date: 17-Oct-2013
https://dl.acm.org/doi/10.1007/978-3-642-41398-8_24
Meng JWu LWang XLin T(2011)Granulation-based symbolic representation of time series and semi-supervised classificationComputers & Mathematics with Applications10.1016/j.camwa.2011.09.00662:9(3581-3590)Online publication date: 1-Nov-2011
https://dl.acm.org/doi/10.1016/j.camwa.2011.09.006
Show More Cited By

Abstract

Cited By

Index Terms

Recommendations

Representation of the Fourier Transform by Fourier Series

Fourier transform representation by frequency-time wavelets

Short-time fractional fourier transform and its applications

Comments

Information

Published In

Publisher

Publication History

Qualifiers

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

View options

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations