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April 24, 2026IoT0 citationsOpen Access

PatternStudio: Neuro-Symbolic Framework for Complex Event Processing

PatternStudio: A Neuro-Symbolic Framework for Dynamic and High-Throughput Complex Event Processing

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Authors

JRJesús Rosa-Bilbao

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Overview

Prototype demonstrates high throughput and low latency in complex event processing using natural language specifications, suggesting improved usability in various domains.

Key Points

  • This research aims to enhance complex event processing (CEP) by simplifying the authoring of temporal rules and deployment workflows.
  • Developed a neuro-symbolic framework called PatternStudio for CEP.
  • Translated natural language specifications into validated event-processing patterns.
  • Evaluated performance on a single-node system using Apache Flink with a focus on throughput and latency.
  • Achieved 47,910 events per second with 250 active rules.
  • Maintained memory usage between 1.6 GB and 1.9 GB during operations.
  • Identified throughput degradation beyond 500 active rules due to CPU saturation.
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Cite This Study

Jesús Rosa-Bilbao (2026) studied this question.

synapsesocial.com/papers/69eb0aeb553a5433e34b4ce0https://doi.org/10.3390/iot7020036
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