Title :
An effective subsequence-to-subsequence time series matching approach
Author :
Bettaiah, Vineetha ; Ranganath, Heggere S.
Author_Institution :
Comput. Sci. Dept., Univ. of Alabama in Huntsville, Huntsville, AL, USA
Abstract :
The success of time series data mining applications, such as query by content, clustering, and classification, is greatly determined by the performance of the algorithm used for the determination of similarity between two time series. The previous research on time series matching has mainly focused on whole sequence matching and sequence-to-subsequence matching. Relatively, very little work has been done on subsequence-to-subsequence matching, where two time series are considered similar if they contain similar subsequences or patterns in the same time order. This paper presents an effective approach capable of handling whole sequence, sequence-to-subsequence and subsequence-to-subsequence matching. The proposed approach derives its strength from the novel two stage segmentation algorithm, which facilitates aligning the two time series by retaining perceptually important points in both time series as break points.
Keywords :
data mining; pattern matching; time series; pattern matching; sequence handling; subsequence-to-subsequence time series matching approach; time series data mining applications; two-stage segmentation algorithm; Approximation methods; Discrete Fourier transforms; Piecewise linear approximation; Programmable logic arrays; Time measurement; Time series analysis; Vectors; Subsequence to subsequence matching; Time Series Matching; Time Series Representation; Time Series Segmentation;
Conference_Titel :
Science and Information Conference (SAI), 2014
Conference_Location :
London
Print_ISBN :
978-0-9893-1933-1
DOI :
10.1109/SAI.2014.6918179