Abstract
Stream Reasoning is set at the confluence of Artificial Intelligence and Stream Processing with the ambitious goal to reason on rapidly changing flows of information. The goals of the lecture are threefold: (1) Introducing students to the state-of-the-art of Stream Reasoning, (2) Deep diving into RDF Stream Processing by outlining how to design, develop and deploy a stream reasoning application, and (3) Jointly discussing the limits of the state-of-the-art and the current challenges.
Cite
CITATION STYLE
Falzone, E., Tommasini, R., & Della Valle, E. (2020). Stream Reasoning: From Theory to Practice. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12258 LNCS, pp. 85–108). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-60067-9_4
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