Discovering hierarchical index structures in time series archives

Author

Artail, Hassan A.

Author_Institution

Dept. of Electr. & Comput. Eng., American Univ. of Beirut, Lebanon

fYear

2003

fDate

11-13 Aug. 2003

Firstpage

108

Lastpage

112

Abstract

We describe an algorithm that uses feature detection as the basis for discovering index parameters within temporal data archives that comprise multiple time series. The detection of features is accomplished using the Haar wavelet transform. We focus on the discontinuities whose number and location within each series are used to extract index information and then build a hierarchy of index vectors. We present a client application that applies the algorithm to automotive test data archives.

Keywords

Haar transforms; data mining; database indexing; feature extraction; temporal databases; time series; wavelet transforms; Haar wavelet transform; automotive test data archives; data indexing; data segmentation; discontinuity detection; feature detection; hierarchical index structure discovery; temporal data archives; time series archives; Computer vision; Data mining; Discrete wavelet transforms; Indexing; Noise reduction; Sensor arrays; Sensor phenomena and characterization; Signal resolution; Wavelet coefficients; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology: Research and Education, 2003. Proceedings. ITRE2003. International Conference on

Print_ISBN

0-7803-7724-9

Type

conf

DOI

10.1109/ITRE.2003.1270583

Filename

1270583