案例表示是案例推理的基础,突发事件案例涉及到大量非结构化的信息,如何有效地将海量信息整合成案例是案例表示的关键。该文针对中国突发事件的特点,结合信息来源,给出了突发事件案例应包括的要素,针对结构化信息和非结构化信息提出了不同的表示方法。对于结构化信息,使用模糊集合的方法定量表示,以隶属度函数代替单一的数值; 对于非结构化的文本信息,通过对3种关键词提取方法的比较研究,选择了基于词语共现概率的改进方法提取关键词,利用提取结果进行信息抽取。整个案例被表示成包含定量化数据和抽取文本的半结构化形式,前者主要用于案例匹配,后者记录了案例的详细内容,用于提供决策支持。这种表示方法为进一步的案例推理奠定了基础。

Case representation is the basis for case-based reasoning. The representation should efficiently organize large amounts of information which is usually unstructured information, related to the emergency cases. This paper describes the attributes that should be included in emergency case descriptions with a case framework based on analyses of emergency events and information with both structured and unstructured information. The structured information uses fuzzy sets to describe the non-quantitative data using memberships instead of numerical values. The unstructured information is analyzed by three algorithms for keyword extraction with the word co-occurrence approach chosen as the best. The extracted keywords are then used to obtain the proper information segments for the unstructured part of the emergency case. The whole case is represented in a semi-structured form with quantitative attributes used in the case retrieval and text data used in the case reasoning. The results show that this approach gives good results as a foundation for case-based reasoning applications.