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Cluster Computing
Published in: Cluster Computing 3/2019

08-12-2017

A novel time series behavior matching algorithm for online conversion algorithms

Authors: Iftikhar Ahmad, Javeria Iqbal

Published in: Cluster Computing | Special Issue 3/2019

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Abstract

This work presents a novel time series behavior matching algorithm for analyzing behavior (trend) similarity between two given time series. Unlike traditional approaches, our dynamic programming based approach “Behavior Matching (BM)” is based on trends and behavior rather than absolute distance as similarity measure. In order to compare the effectiveness of our proposed algorithm, we conduct an experimental study on real world stock data (DAX30). We compare our proposed algorithm with state-of-the-art algorithm Euclidean Distance, V-Shift and Dynamic Time Warping. The experimental results validates the performance guarantee and consistency of our proposed scheme.
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Metadata
Title
A novel time series behavior matching algorithm for online conversion algorithms
Authors
Iftikhar Ahmad
Javeria Iqbal
Publication date
08-12-2017
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 3/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-1481-4

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