Conference Proceedings

An automated matrix profile for mining consecutive repeats in time series

M Mirmomeni, Y Kowsar, L Kulik, J Bailey

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Springer Nature | Published : 2018

Abstract

© Springer International Publishing AG, part of Springer Nature 2018. A key application of wearable sensors is remote patient monitoring, which facilitates clinicians to observe patients non-invasively, by examining the time series of sensor readings. For analysis of such time series, a recently proposed technique is Matrix Profile (MP). While being effective for certain time series mining tasks, MP depends on a key input parameter, the length of subsequences for which to search. We demonstrate that MP’s dependency on this input parameter impacts its effectiveness for finding patterns of interest. We focus on finding consecutive repeating patterns (CRPs), which represent human activities and..

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