基于属性实例集合语义相似的模式匹配

近年来，模式匹配作为Web信息集成管理与应用中的重要问题，得到了广泛关注和研究。已有模式匹配方法大多是基于模式信息的，对数据实例信息利用则较少。针对数据集成环境下模式信息不全或存在冲突的模式信息导致模式匹配结果不正确的问题，给出了计算属性间语义相似性的方法以提高模式匹配的性能，分析了模式内语义相近多属性间的语义差别，进一步给出了基于带权二分图最大化算法的模式匹配方法。通过实验，说明基于实例集合语义相似的模式匹配方法能在模式信息不全面或存在冲突的情况下，得到更完整、更准确的模式匹配。

Schema Mapping Based on Semantic Similarity of Data Instances Sets

Schema mapping, as the important issue in Web integrated information management and application, has been widely concerned and researched in recent years. Most schema mapping methods have been implemented based on schema information,and schema mapping methods based on data instances are rare. There are many cases in which schema information is insufficient or conflict, and incorrect schema mapping method may be got. In order to improve the performance of schema mapping,a measure was proposed to evaluate semantic similarity between attributes,also the semantic difference between two semantic similarattributes in the same schema was analyzed. Further, a mapping approach based on weighted bipartite was proposed. hhe mapping method proposed was evaluated with experiments and was verified to be efficient and effective to obtain the more complete and accurate schema mapping in situations where schema information is incomplete or conflicting.