Abstract
The rapid change and heterogeneity of today’s generated data calls for real-time decision making systems that can cope with the presented heterogeneity. In this paper, we present an Ontology Based Event Processing system that bridges the gap between ontology-based reasoning and event processing. We propose both a language and an architecture to perform event processing over abstract ontology concepts. This allows to perform efficient temporal reasoning, while the high-level ontological definitions reduce the need for knowledge of the underlying data structure in complex domains.
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Tommasini, R., Bonte, P., Della Valle, E., Mannens, E., De Turck, F., & Ongenae, F. (2017). Towards ontology-based event processing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10161 LNCS, pp. 115–127). Springer Verlag. https://doi.org/10.1007/978-3-319-54627-8_9
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