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Early classification of spatio-temporal events using partial information

This paper investigates event extraction and early event classification in contiguous spatio-temporal data streams, where events need to be classified using partial information, i.e. while the event is ongoing. The framework incorporates an event extraction algorithm and an early event classificatio...

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Detalles Bibliográficos
Autores principales: Kandanaarachchi, Sevvandi, Hyndman, Rob J., Smith-Miles, Kate
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7406362/
https://www.ncbi.nlm.nih.gov/pubmed/32756613
http://dx.doi.org/10.1371/journal.pone.0236331
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author Kandanaarachchi, Sevvandi
Hyndman, Rob J.
Smith-Miles, Kate
author_facet Kandanaarachchi, Sevvandi
Hyndman, Rob J.
Smith-Miles, Kate
author_sort Kandanaarachchi, Sevvandi
collection PubMed
description This paper investigates event extraction and early event classification in contiguous spatio-temporal data streams, where events need to be classified using partial information, i.e. while the event is ongoing. The framework incorporates an event extraction algorithm and an early event classification algorithm. We apply this framework to synthetic and real problems and demonstrate its reliability and broad applicability. The algorithms and data are available in the R package eventstream, and other code in the supplementary material.
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spelling pubmed-74063622020-08-13 Early classification of spatio-temporal events using partial information Kandanaarachchi, Sevvandi Hyndman, Rob J. Smith-Miles, Kate PLoS One Research Article This paper investigates event extraction and early event classification in contiguous spatio-temporal data streams, where events need to be classified using partial information, i.e. while the event is ongoing. The framework incorporates an event extraction algorithm and an early event classification algorithm. We apply this framework to synthetic and real problems and demonstrate its reliability and broad applicability. The algorithms and data are available in the R package eventstream, and other code in the supplementary material. Public Library of Science 2020-08-05 /pmc/articles/PMC7406362/ /pubmed/32756613 http://dx.doi.org/10.1371/journal.pone.0236331 Text en © 2020 Kandanaarachchi et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Kandanaarachchi, Sevvandi
Hyndman, Rob J.
Smith-Miles, Kate
Early classification of spatio-temporal events using partial information
title Early classification of spatio-temporal events using partial information
title_full Early classification of spatio-temporal events using partial information
title_fullStr Early classification of spatio-temporal events using partial information
title_full_unstemmed Early classification of spatio-temporal events using partial information
title_short Early classification of spatio-temporal events using partial information
title_sort early classification of spatio-temporal events using partial information
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7406362/
https://www.ncbi.nlm.nih.gov/pubmed/32756613
http://dx.doi.org/10.1371/journal.pone.0236331
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