On Event-Driven Knowledge Graph Completion in Digital Factories
원문 초록
Smart factories are equipped with machines that can sense their manufacturing environments, interact with each other, and control production processes. Smooth operation of such factories requires that the machines and engineering personnel that conduct their monitoring and diagnostics share a detailed common industrial knowledge about the factory, e.g., in the form of knowledge graphs. Creation and maintenance of such knowledge is expensive and requires automation. In this work we show how machine learning that is specifically tailored towards industrial applications can help in knowledge graph completion. In particular, we show how knowledge completion can benefit from event logs that are common in smart factories. We evaluate this on the knowledge graph from a real world-inspired smart factory with encouraging results.
함께 살펴볼 논문
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Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs
GenIC: An LLM-Based Framework for Instance Completion in Knowledge Graphs
ReCDAP: Relation-Based Conditional Diffusion with Attention Pooling for Few-Shot Knowledge Graph Completion
Knowledge Graph Completion with Mixed Geometry Tensor Factorization
TRIX: A More Expressive Model for Zero-shot Domain Transfer in Knowledge Graphs
Diffusion-based Hierarchical Negative Sampling for Multimodal Knowledge Graph Completion
토론
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