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Schema matching based on SQL statements

机译:基于SQL语句的模式匹配

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摘要

Schema matching is a critical step in numerous database applications such as web data sources integrating, data warehouse loading and information exchanging among several authorities. In this paper, we propose to exploit the similarities of the SQL statements in the query logs to find the correspondences between attributes in the schemas to be matched. We discover three kinds of similarities which benefit schema matching, that is, the similarity of clauses itself, the similarity of the frequency of clauses occurring in different SQL statements and the similarity of statistics about the relationship among clauses. We combine the clauses related to the similarities into a graph, and then transform the task of matching attributes into the problem of matching the graphs. Through matching the graphs, we obtain a set of attribute sequence pairs with the similarity score. Actually, each sequence pair represents a set of correspondences. Next, we exploit the techniques from the quadratic programming field to decompose the sequence pairs into correspondences, that is, to obtain the similarity score of each correspondence. Finally, an efficient method is used to choose the best correspondence for each attribute from the candidate set. The experimental study shows that the proposed approach is effective and its combination with other matchers has good performance.
机译:模式匹配是众多数据库应用程序中的关键步骤,例如Web数据源集成,数据仓库加载以及多个机构之间的信息交换。在本文中,我们建议利用查询日志中SQL语句的相似性来查找要匹配的模式中属性之间的对应关系。我们发现了三种有益于模式匹配的相似性,即子句本身的相似性,不同SQL语句中出现的子句出现频率的相似性以及有关子句之间关系的统计信息的相似性。我们将与相似性相关的子句组合成一个图,然后将匹配属性的任务转换为匹配图的问题。通过匹配图,我们获得了具有相似性得分的一组属性序列对。实际上,每个序列对代表一组对应关系。接下来,我们利用来自二次编程领域的技术将序列对分解为对应关系,即获得每个对应关系的相似性得分。最后,使用一种有效的方法从候选集中为每个属性选择最佳对应关系。实验研究表明,该方法是有效的,并且与其他匹配器组合具有良好的性能。

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