Processing flows of information: From data stream to complex event processing

By Gianpaolo Cugola, Alessandro Margara. CSUR, 2012

1,027 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/dab11c890b9924c8bfcb09bf8a9b1fbd1e2bbffc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. José Angel Carvajal Soto
2. Miriam A. M. Capretz
3. Davy Preuveneers
4. E. Zudor
5. Marc Jentsch

In Computer Networks and Communications

1. José Angel Carvajal Soto
2. Alexandra L’Heureux
3. Miriam A. M. Capretz
4. Davy Preuveneers
5. Katarina Grolinger
6. Hany F. ElYamany
7. E. Zudor
8. Marc Jentsch

In Signal Processing

1. José Angel Carvajal Soto
2. Davy Preuveneers
3. E. Zudor
4. Marc Jentsch

Citations in the corpus

• CEML: Mixing and moving complex event processing and machine learning to the edge of the network for IoT applications (2016, methodology): “Finally, the protocol must provide tools to handle the pub/sub characteristics of the CEP engines.”
• An event-driven manufacturing information system architecture for Industry 4.0 (2017, background): “CEP formalizes how patterns and knowledge are identified from a flow of low-level events, which results in high-level events (Cugola and Margara 2012).”
• Machine Learning With Big Data: Challenges and Approaches (2017, background): “Gorawski et al. [89] and Cugola and Margara [90] surveyed data stream processing tools and complex event processing.”