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.
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.