Effective Frequent Motif Discovery for Long Time Series Classification: A Study using Phonocardiogram



Alhijailan, Hajar and Coenen, Frans ORCID: 0000-0003-1026-6649
(2019) Effective Frequent Motif Discovery for Long Time Series Classification: A Study using Phonocardiogram. In: 11th International Conference on Knowledge Discovery and Information Retrieval, 2019-9-17 - 2019-9-19.

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Abstract

A mechanism for extracting frequent motifs from long time series is proposed, directed at classifying phono-cardiograms. The approach features two preprocessing techniques: silent gap removal and a novel candidate frequent motif discovery mechanism founded on the clustering of time series subsequences. These techniques were combined into one process for extracting discriminative frequent motifs from single time series and then to combine these to identify a global set of discriminative frequent motifs. The proposed approach compares favourably with these existing approaches in terms of accuracy and has a significantly improved runtime.

Item Type: Conference or Workshop Item (Unspecified)
Uncontrolled Keywords: Time and Point Series Analysis, Frequent Motifs, Data Preprocessing, Classification, Phonocardiogram
Depositing User: Symplectic Admin
Date Deposited: 12 Sep 2019 07:54
Last Modified: 19 Jan 2023 00:26
DOI: 10.5220/0008018902660273
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3054272