Fast subsequence search on time series data

Yuhong Li; Bo Tang; Leong Hou U; Man Lung Yiu; Zhiguo Gong

doi:10.5441/002/edbt.2017.58

Fast subsequence search on time series data

Yuhong Li, Bo Tang, Leong Hou U, Man Lung Yiu, Zhiguo Gong

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

5 Citations (Scopus)

Abstract

Many applications on time series data require solving the subsequence search problem, which has been extensively studied in the database and data mining communities. These applications are computation bound rather than disk I/O bound. In this work, we further propose effective and cheap lower-bounds to reduce the computation cost of the subsequence search problem. Experimental studies show that the proposed lower-bounds can boost the performance of the state-of-the-art solution by up to an order of magnitude.

Original language	English
Title of host publication	Advances in Database Technology - EDBT 2017
Subtitle of host publication	20th International Conference on Extending Database Technology, Proceedings
Publisher	OpenProceedings.org
Pages	514-517
Number of pages	4
Volume	2017-March
ISBN (Electronic)	9783893180738
DOIs	https://doi.org/10.5441/002/edbt.2017.58
Publication status	Published - 1 Jan 2017
Event	20th International Conference on Extending Database Technology, EDBT 2017 - Venice, Italy Duration: 21 Mar 2017 → 24 Mar 2017

Conference

Conference	20th International Conference on Extending Database Technology, EDBT 2017
Country/Territory	Italy
City	Venice
Period	21/03/17 → 24/03/17

ASJC Scopus subject areas

Information Systems
Software
Computer Science Applications

More information

10.5441/002/edbt.2017.58

Cite this

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title = "Fast subsequence search on time series data",

abstract = "Many applications on time series data require solving the subsequence search problem, which has been extensively studied in the database and data mining communities. These applications are computation bound rather than disk I/O bound. In this work, we further propose effective and cheap lower-bounds to reduce the computation cost of the subsequence search problem. Experimental studies show that the proposed lower-bounds can boost the performance of the state-of-the-art solution by up to an order of magnitude.",

author = "Yuhong Li and Bo Tang and {Hou U}, Leong and Yiu, {Man Lung} and Zhiguo Gong",

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volume = "2017-March",

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Li, Y, Tang, B, Hou U, L, Yiu, ML & Gong, Z 2017, Fast subsequence search on time series data. in Advances in Database Technology - EDBT 2017: 20th International Conference on Extending Database Technology, Proceedings. vol. 2017-March, OpenProceedings.org, pp. 514-517, 20th International Conference on Extending Database Technology, EDBT 2017, Venice, Italy, 21/03/17. https://doi.org/10.5441/002/edbt.2017.58

Fast subsequence search on time series data. / Li, Yuhong; Tang, Bo; Hou U, Leong et al.
Advances in Database Technology - EDBT 2017: 20th International Conference on Extending Database Technology, Proceedings. Vol. 2017-March OpenProceedings.org, 2017. p. 514-517.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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M3 - Conference article published in proceeding or book

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Fast subsequence search on time series data

Abstract

Conference

ASJC Scopus subject areas

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