Schema matching is a basic operation in data integration and schema integration process .Due to autonomy and heterogeneity of data sources , uncertainty is an inherent characteristic of schema matching process .In order to enhance the efficiency of uncertain schema matching, the paper proposes an ordered weighted average (OWA) operator based uncertain matching solution .First of all it provides a data model to represent uncertainty in schema matching process , taking that as its basis it introduces three matching solutions for different schemas.Then by taking advantage of OWA operator it aggregates the results of different matchers .At last by experiment results the feasibility and effectiveness of the solution is validated .%模式匹配是数据集成和模式集成过程中一个基本操作。由于数据源的自治性和异构性，不确定性是模式匹配过程固有的本质特性。为了提升不确定模式匹配的效率，提出一种基于有序加权平均OWA（Ordered Weighted Averaging ）算子的不确定性匹配方法。首先给出一个模式匹配过程中表示不确定性的数据模型，在此基础上介绍三种不同的模式匹配方法。利用有序加权平均算子，聚合不同匹配器的结果。最后通过实验结果证明了方法的可行性和有效性。
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