A data-type-based approach for identifying corresponding attributes in heterogeneous databases

In order to support interoperability among databases, the probability and efficiency of using metadata and data contents to automate some aspect of semantic integration become a key challenge. An important task of semantic integration in heterogeneous database is to determine which fields refer to the same data. Although many methods can be employed to automate the process, we argue that the existing methods of identifying corresponding attributes are time-consuming. In this paper we contribute to lower time complexity without reducing the precision ratio and recall ratio by providing a more efficient method, a data-type-based approach, to identify corresponding attributes in heterogeneous databases. The experimental results showed our method is effective.