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Early classification of spatio-temporal events using partial information.


ABSTRACT: 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.

SUBMITTER: Kandanaarachchi S 

PROVIDER: S-EPMC7406362 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Early classification of spatio-temporal events using partial information.

Kandanaarachchi Sevvandi S   Hyndman Rob J RJ   Smith-Miles Kate K  

PloS one 20200805 8


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 oth  ...[more]

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