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Complex event recognition in the Big Data era: a survey

Giatrakos Nikolaos, Alevizos Elias, Artikis, Alexander, Deligiannakis Antonios, Garofalakis Minos

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URIhttp://purl.tuc.gr/dl/dias/1F9754C3-04F4-4682-B39D-58A936FA1E49-
Identifierhttps://doi.org/10.1007/s00778-019-00557-w-
Identifierhttps://link.springer.com/article/10.1007%2Fs00778-019-00557-w-
Languageen-
Extent40 pagesen
TitleComplex event recognition in the Big Data era: a surveyen
CreatorGiatrakos Nikolaosen
CreatorΓιατρακος Νικολαοςel
CreatorAlevizos Eliasen
CreatorArtikis, Alexanderen
CreatorDeligiannakis Antoniosen
CreatorΔεληγιαννακης Αντωνιοςel
CreatorGarofalakis Minosen
CreatorΓαροφαλακης Μινωςel
PublisherSpringer Natureen
Content SummaryThe 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.en
Type of ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2021-09-29-
Date of Publication2020-
SubjectBig Dataen
SubjectComplex event recognitionen
SubjectComplex event recognition languagesen
SubjectParallelismen
SubjectElasticityen
SubjectDistributed processingen
Bibliographic CitationN. Giatrakos, E. Alevizos, A. Artikis, A. Deligiannakis, and M. Garofalakis, “Complex event recognition in the Big Data era: a survey,” VLDB J., vol. 29, no. 1, pp. 313–352, Jan. 2020. doi: 10.1007/s00778-019-00557-wen

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