| 安璐,杨楚嫣.基于案例推理的应急处置建议生成[J].情报工程,2025,11(4):003-014 |
| 基于案例推理的应急处置建议生成 |
| Emergency Disposal Suggestion Generation Based on Case-based Reasoning |
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| DOI： |
| 中文关键词: 事件原因图谱；建议生成；案例推理；突发事件案例库；应急处置；检索增强生成 |
| 英文关键词: Event Cause Graph; Recommendation Generation; Case-based Reasoning; Public Event Case Database; Emergency Response; RAG |
| 基金项目:国家自然科学基金面上项目“危机情境下网络信息传播失序识别与干预方法研究”（72174153）；国家自然科学基金创新研究群体项目“信息资源管理”（71921002）。 |
| 作者 | 单位 | | 安璐 | 1.武汉大学信息资源研究中心 武汉 430072；2.武汉大学信息管理学院 武汉 430072；3.武汉大学数据智能研究院 武汉 430072 | | 杨楚嫣 | 武汉大学信息管理学院 武汉 430072 |
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| 中文摘要: |
| [目的/意义] 构建实现情境特征与事理规则融合的案例表征体系，突破传统案例推理方法在方案重用方面的局限，为应急决策领域提供更具针对性和可解释性的智能支持。[方法/过程]在基于案例的推理框架下，将突发事件知识图谱与事件原因图谱相结合，构建突发事件案例库；在案例检索与重用阶段，基于图谱和语义相似度匹配历史案例，采用图谱增强的检索增强生成机制将案例知识作为大语言模型补充上下文，生成针对目标突发事件的致因推断、风险分析及应急处置建议。[结果/结论] 研究提出的框架能有效支持多维度案例匹配与决策推理，为突发事件应急决策提供兼具情境适配性与规律可解释性的解决方案。 |
| 英文摘要: |
| [Objective/Significance] This study seeks to develop an integrated case representation framework that combines contextual features with causal principles, overcoming the limitations of conventional case-based reasoning methods in solution reuse. The proposed approach aims to provide more targeted and interpretable intelligent support for emergency decisionmaking.[Methods/Processes] Within a case-based reasoning framework, this study integrate emergency knowledge graphs with causal event graphs to construct a comprehensive case repository. During case retrieval and reuse, our graph-enhanced retrieval-augmented generation mechanism leverages both graph-based and semantic similarity matching to identify relevant historical cases. These retrieved cases serve as contextual supplements for large language models, enabling the generation of causal inferences, risk assessments, and targeted emergency response recommendations for newly occurring incidents. [Results/Conclusions] The proposed framework effectively facilitates multi-dimensional case matching and decision reasoning, delivering emergency response solutions that are both contextually adaptive and interpretable in their underlying logic. |
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