失散人员时空信息模糊匹配模型

失散人员时空信息数量多、失散信息地点的收集和查询较复杂,现有的网络寻亲平台虽具有信息采集快,应用普及范围广的特点,但对于失散人员的信息管理较分散,缺乏结合时间范畴和空间范畴的分析。本文在失散人员属性信息查询的基础上,针对失散信息的不准确性和模糊性,对不同失踪年龄段人员进行记忆模糊度分析,并结合汉语言分区以及模糊时空范围设置阈值和权重,建立失散人员时空信息模糊匹配模型。该模型根据失散孩子姓名、性别、血型、出生时间、失踪时间、失踪地点、方言口音及失踪年龄段的模糊特征等影响因子,综合计算出失散人员之间的信息匹配指数;并利用时间地理学方法设计了模型的时空修正方法,对匹配结果的时空可达范围是否存在交集进行了检验。案例数据验证结果表明,该模型能综合考虑已知的失散人员匹配指标项,可筛选出匹配程度较高的信息。

A Fuzzy Matching Model of Spatial-temporal Information of Dispersed Person

In recent years, a large number of lost persons have aroused the attention of all sectors of society because the collection and query of information is not easy. The network tracing platform is fast in information acquisition and has widely used in the application. However, the information management of lost persons are scattered, and it is insufficient in the spatial and temporal category analysis. To solve the problems of the inaccuracy and ambiguity of information, we made the memory fuzziness analysis of different age groups of lost persons based on the query of their attribute information. Then, combining with the partition of Chinese language and the fuzzy range of space and time, we set threshold and weight for matching algorithm. Finally, we set up the fuzzy matching model for spatial-temporal information of lost persons. Considering several characteristics of the lost people information such as names, gender, blood types, date of birth, missing time, missing place, dialect accent and missing age, we computed the information matching index among the lost persons. In addition, we used the time geography method to design the time correction method of the model and we also verified the intersection of spatiotemporal reachable range of matching results. The results of case verification indicated that the model can consider the known items of matching index and select the information that has higher matching degree.