TY - JOUR
TI - Complex event recognition in the Big Data era: a survey
AU - Giatrakos, N.
AU - Alevizos, E.
AU - Artikis, A.
AU - Deligiannakis, A.
AU - Garofalakis, M.
JO - The VLDB Journal
PY - 2020
VL - 29
TODO - 1
SP - 313-352
PB - Springer-Verlag
SN - 1066-8888, 0949-877X
TODO - 10.1007/s00778-019-00557-w
TODO - Algorithmic languages;  Elasticity;  Surveys, Cardiac arrhythmia;  Complex events;  Computational paradigm;  Distributed processing;  Future research directions;  Maritime surveillance;  Parallelism;  Proactive measures, Big data
TODO - The concept of event processing is established as a generic computational paradigm in various application fields. Events report on state changes of a system and its environment. Complex event recognition (CER) refers to the identification of composite events of interest, which are collections of simple, derived events that satisfy some pattern, thereby providing the opportunity for reactive and proactive measures. Examples include the recognition of anomalies in maritime surveillance, electronic fraud, cardiac arrhythmias and epidemic spread. This survey elaborates on the whole pipeline from the time CER queries are expressed in the most prominent languages, to algorithmic toolkits for scaling-out CER to clustered and geo-distributed architectural settings. We also highlight future research directions. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.
ER -