CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
Complex event recognition in the Big Data era: a survey
Authors
N. Giatrakos Alevizos, E. Artikis, A. Deligiannakis, A. Garofalakis, M.
Publication date
1 January 2020
Publisher
Abstract
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
Similar works
Full text
Available Versions
Pergamos : Unified Institutional Repository / Digital Library Platform of the National and Kapodistrian University of Athens
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:lib.uoa.gr:uoadl:3071289
Last time updated on 10/02/2023