Abstract: A generalized matching method for entity matching, vector data contrast method based on probabilistic theory and compound criteria, was proposed. The method extended from traditional single criteria to compound criteria, and the attributes information, spatial information and graphical information of vector data were considered. In addition, it attempted to resolve one-many and many-many matching relationships. The experimental results indicate that this method has good precision and recall, and contrastive results are available for the incremental analysis of geographic datasets.

Key words: probabilistic theory, entity matching, data contrasting, compound criteria, incremental updating

摘要： 提出了一种广义的空间实体对比匹配算法──基于概率及复合指标的矢量数据对比算法。该算法由传统匹配单个指标扩展到多个指标，综合考虑矢量数据的属性、空间和图形信息，融合了多种信息指标，并能有效解决非一对一的匹配情况。实验结果表明该方法具有良好的精度和召回率，对比结果可有效应用于矢量地图数据的增量更新。

关键词: 概率理论, 实体匹配, 数据对比, 复合指标, 增量更新