An open architecture for complex event processing with machine learning

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Luong, Nhan Nathan Tri
Milosevic, Zoran
Berry, Andrew
Rabhi, Fethi
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2020
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Eindhoven, Netherlands

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Abstract

This paper proposes an advanced, open architecture to augment streaming data platforms with both complex event processing (CEP) and predictive machine learning models. We leverage the power of CEP to preprocess streams using sophisticated event pattern expressions then present these preprocessed streams for downstream training and predictive computations. We demonstrate this approach using specific technology components.

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2020 IEEE 24th International Enterprise Distributed Object Computing Conference (EDOC)

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Information and computing sciences

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Computer Science, Software Engineering

Computer Science, Theory & Methods

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Luong, NNT; Milosevic, Z; Berry, A; Rabhi, F, An open architecture for complex event processing with machine learning, 2020 IEEE 24th International Enterprise Distributed Object Computing Conference (EDOC), 2020, pp. 51-56