Performance Evaluation of LLMs in Automated RDF Knowledge Graph Generation
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arXiv:2603.29878v1 Announce Type: cross
Abstract: Cloud systems generate large, heterogeneous log data containing critical infrastructure, application, and security information. Transforming these logs into RDF triples enables their integration into knowledge graphs, improving interpretability, root-cause analysis, and cross-service reasoning beyond what raw logs allow. Large Language Models (LLMs) offer a promising approach to automate RDF knowledge graph generation; however, their effectivene
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Performance Evaluation
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Performance Evaluation is a quarterly peer-reviewed scientific journal covering modeling, measurement, and evaluation of performance aspects of computing and communications systems. The editor-in-chief is Giuliano Casale (Imperial College London). The journal was established in 1981 and is published...
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arXiv:2603.29878v1 Announce Type: cross
Abstract: Cloud systems generate large, heterogeneous log data containing critical infrastructure, application, and security information. Transforming these logs into RDF triples enables their integration into knowledge graphs, improving interpretability, root-cause analysis, and cross-service reasoning beyond what raw logs allow. Large Language Models (LLMs) offer a promising approach to automate RDF knowledge graph generation; however, their effectivene
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