Schema Mapping Based on Semantic Similarity of Data Instances Sets
基于属性实例集合语义相似的模式匹配

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.