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Logic-based event recognition

Published online by Cambridge University Press:  12 November 2012

Alexander Artikis ,
Anastasios Skarlatidis ,
François Portet  and
Georgios Paliouras
Alexander Artikis
Affiliation:
Institute of Informatics and; Telecommunications, NCSR “Demokritos”, Athens 15310, Greece; e-mail: paliourg@iit.demokritos.gr, anskarl@iit.demokritos.gr
Anastasios Skarlatidis
Affiliation:
Institute of Informatics and; Telecommunications, NCSR “Demokritos”, Athens 15310, Greece; e-mail: paliourg@iit.demokritos.gr, anskarl@iit.demokritos.gr Department of Information and Communication Systems Engineering, University of the Aegean, Greece
François Portet
Affiliation:
Laboratoire d'Informatique de Grenoble, CNRS/UJF/INPG/UPMF UMR 5217, F-38041 Grenoble, France; e-mail: Francois.Portet@imag.fr
Georgios Paliouras
Affiliation:
Institute of Informatics and; Telecommunications, NCSR “Demokritos”, Athens 15310, Greece; e-mail: paliourg@iit.demokritos.gr, anskarl@iit.demokritos.gr
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Abstract

Today's organizations require techniques for automated transformation of their large data volumes into operational knowledge. This requirement may be addressed by using event recognition systems that detect events/activities of special significance within an organization, given streams of ‘low-level’ information that is very difficult to be utilized by humans. Consider, for example, the recognition of attacks on nodes of a computer network given the Transmission Control Protocol/Internet Protocol messages, the recognition of suspicious trader behaviour given the transactions in a financial market and the recognition of whale songs given a symbolic representation of whale sounds. Various event recognition systems have been proposed in the literature. Recognition systems with a logic-based representation of event structures, in particular, have been attracting considerable attention, because, among others, they exhibit a formal, declarative semantics, they have proven to be efficient and scalable and they are supported by machine learning tools automating the construction and refinement of event structures. In this paper, we review representative approaches of logic-based event recognition and discuss open research issues of this field. We illustrate the reviewed approaches with the use of a real-world case study: event recognition for city transport management.

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Articles
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The Knowledge Engineering Review , Volume 27 , Issue 4 , December 2012 , pp. 469 - 506
Copyright
Copyright © Cambridge University Press 2012

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