Journal article

Early classification of spatio-temporal events using partial information

Sevvandi Kandanaarachchi, Rob J Hyndman, Kate Smith-Miles

PLOS ONE | PUBLIC LIBRARY SCIENCE | Published : 2020

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.

University of Melbourne Researchers

Grants

Awarded by Australian Research Council


Funding Acknowledgements

Funding was provided by the Australian Research Council through the Linkage Project LP160101885. Initials of authors who received the award: KSM, RJH https://www.arc.gov.au/.The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Funding was provided by the Australian Research Council through the Linkage Project LP160101885.