Multi-Field Hybrid Retrieval-Augmented Generation for Maritime Accident Root Cause Analysis
Maritime accident adjudication reports contain critical tribunal findings for root cause analysis (RCA), yet retrieving relevant precedents and drafting consistent reports from decades of records remains labor-intensive. This paper proposes a multi-field hybrid retrieval-augmented generation (RAG) framework for automated maritime RCA, utilizing a comprehensive dataset of 13,329 Korea Maritime Safety Tribunal (KMST) reports (1971-2025). We transform raw adjudications into a structured knowledge base of "incident cards", indexing three distinct fields-Summary, Causes, and Disposition-alongside a hierarchical L1/L2 cause taxonomy. Our retrieval strategy employs a field-aware hybrid approach,...
| Authors | Seongjin Kim, Sungil Kim |
|---|---|
| Primary category | cs.AI |
| Published | 11 June 2026 |
| Last updated at source | 11 June 2026 |
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