AgentOnto, 온톨로지 기반 엔터프라이즈 데이터 분석 에이전트
AgentOnto: Ontology-Guided LLM Agents for Enterprise Data Analytics
- 매체
- Takara TLDR
- 게시
- 중요도
- 3/5
- 화제 지수
- —
한국어 요약
온톨로지로 구조화된 데이터베이스·문서·사례 지식을 조직하는 AgentOnto 에이전트가 제안됐다. 반복적 온톨로지 개선으로 엔터프라이즈 분석 신뢰성을 높이고 피드백을 안정적으로 반영한다.
원문 발췌 · English
Enterprise data analysis requires agents to connect analytical requests with knowledge distributed across databases, business documents, and existing example tasks. Without an explicit representation of this knowledge, an agent may produce incorrect analytical results and cannot reliably incorporate feedback. We present AgentOnto, an ontology-guided LLM agent for enterprise data analytics. AgentOnto organizes heterogeneous enterprise knowledge into an ontology that directly guides analysis and incorporates confirmed feedback. Iterative Ontology Preparation further improves the ontology through self-generated analysis tasks. We evaluate AgentOnto on two public data sources. AgentOnto substantially outperforms representative methods, while module-level evaluations confirm the effectiveness of ontology construction, analysis, and updating. A real-world deployment further demonstrates its practical value in enterprise analytics. These results demonstrate that explicitly constructing, using, and updating enterprise knowledge supports reliable and adaptable data analysis.