Abstract: To make up the low efficiency of proof combination method in the exiting schema matching, a new model named Uncertain Schema Matching Model (USMM) was proposed, which can process uncertain schema matching. USMM is a multi-dimensional model. Domain knowledge and proof combination method were applied to process uncertainty of schema matching in order to lower the complexity of matching in USMM. Multi-dimensional structural information of schema was adopted in searching for the inner uncertainty of matching. Formalized definitions of uncertain schema matching and uncertain matching relations were put forward. The case study proves that the model is of high practical value.

Key words: schema matching, uncertainty, domain knowledge, proof combination, uncertain schema matching

摘要： 针对已有模式匹配中证据组合方法效率较低的缺点，提出一个能够处理不确定性模式匹配的模型——USMM(Uncertain Schema Matching Model)。该模型是多维混合模型，其中运用领域知识和证据组合方法处理模式匹配中的不确定性，以降低匹配复杂度；利用模式的多维结构信息挖掘匹配中内在的不确定性；在计算名称相似度的公式中加入可信度来细化匹配的不确定度。最后形式化定义了不确定模式匹配、不确定匹配关系。实例分析证明该模型是可行的，具有较高的实用价值。

关键词: 模式匹配, 不确定性, 领域知识, 证据组合, 不确定模式匹配