AgentOnto
An ontology-guided LLM agent framework that enhances the reliability and adaptability of enterprise data analysis by constructing, using and updating enterprise knowledge ontologies. It comprises three modules: ontology construction, ontology-guided analysis and ontology updating.
Timeline (last 90 days)
AgentOnto is an ontology-guided LLM agent framework that improves the reliability and adaptability of enterprise data analysis by constructing, using and updating an enterprise knowledge ontology.
AgentOnto continuously refines the ontology through an iterative ontology preparation mechanism that leverages self-generated analysis tasks.
AgentOnto was evaluated on two public data sources, and the results show that its performance substantially surpasses representative methods.
AgentOnto was deployed in a real enterprise, demonstrating its practical value.
Module-level ablation experiments verified the effectiveness of each stage—ontology construction, analysis, and updating—with performance dropping significantly after removing any module.
The ontology construction and maintenance costs of AgentOnto have not yet been quantified, and its speed of adaptation to dynamic business remains to be further studied.
AgentOnto's current evaluation focuses on public data sources, and its cross-industry generalization capability requires validation on more cases.
AgentOnto's conclusions rely mainly on internal ablation experiments and a real enterprise deployment as supporting evidence, lacking independent third-party reproduction.
All Facts (8)
AgentOnto's conclusions rely mainly on internal ablation experiments and a real enterprise deployment as supporting evidence, lacking independent third-party reproduction.
50%UnverifiedAgentOnto continuously refines the ontology through an iterative ontology preparation mechanism that leverages self-generated analysis tasks.
50%UnverifiedAgentOnto was evaluated on two public data sources, and the results show that its performance substantially surpasses representative methods.
50%UnverifiedAgentOnto is an ontology-guided LLM agent framework that improves the reliability and adaptability of enterprise data analysis by constructing, using and updating an enterprise knowledge ontology.
50%UnverifiedModule-level ablation experiments verified the effectiveness of each stage—ontology construction, analysis, and updating—with performance dropping significantly after removing any module.
50%UnverifiedThe ontology construction and maintenance costs of AgentOnto have not yet been quantified, and its speed of adaptation to dynamic business remains to be further studied.
50%UnverifiedAgentOnto's current evaluation focuses on public data sources, and its cross-industry generalization capability requires validation on more cases.
50%UnverifiedAgentOnto was deployed in a real enterprise, demonstrating its practical value.
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