Name
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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/EDOC49727.2020.00016 | 2020 IEEE 24th International Enterprise Distributed Object Computing Conference (EDOC) |
Keywords | DocType | ISSN |
streaming,real-time analytics,complex event processing,machine learning,artificial inteligence | Conference | 2325-6354 |
ISBN | Citations | PageRank |
978-1-7281-6474-8 | 0 | 0.34 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nhan Nathan Tri Luong | 1 | 0 | 0.34 |
| Zoran Milosevic | 2 | 548 | 54.38 |
| Andrew Berry | 3 | 0 | 0.34 |
| Fethi Rabhi | 4 | 427 | 50.68 |