Ontology-grounded tool architectures eliminate hallucination of domain identifiers in industrial AI agents by enforcing semantic constraints through a typed relational configuration and three-operation interface.
Towards a formal manufacturing reference ontology
3 Pith papers cite this work. Polarity classification is still indexing.
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A reference model based on ISA-95 and Event Knowledge Graphs plus formalized patterns for automating enrichment of production event data from manufacturing sources, demonstrated on use cases.
Hierarchical clustering generates fog colony candidates from device data; NSGA-II selects subsets optimizing network latency and placement runtime across nine scenarios with up to 137 generations needed to dominate controls.
citing papers explorer
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The Semantic Training Gap: Ontology-Grounded Tool Architectures for Industrial AI Agent Systems
Ontology-grounded tool architectures eliminate hallucination of domain identifiers in industrial AI agents by enforcing semantic constraints through a typed relational configuration and three-operation interface.
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A Reference Model and Patterns for Production Event Data Enrichment
A reference model based on ISA-95 and Event Knowledge Graphs plus formalized patterns for automating enrichment of production event data from manufacturing sources, demonstrated on use cases.
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Genetic-based fog colony optimization hybridized with hierarchical clustering and its influence in the placement of fog services
Hierarchical clustering generates fog colony candidates from device data; NSGA-II selects subsets optimizing network latency and placement runtime across nine scenarios with up to 137 generations needed to dominate controls.