Abstract :
Schema matching, which can find semantic correspondences between elements of two schemas, plays a key role in many applications, such as data warehouse, heterogeneous data sources integration and semantic web. Currently, most schema matching problems are achieved by the similar column names in the schemas to be matched, or common domains in the data stored in the schemas. However, reasonable results can not be obtained by these methods when column names and data values are difficult to explain or "opaque" in schemas. In this paper, a new schema matching algorithm which can discover semantic matches between opaque database schemas is proposed. Compared with the original schema matching algorithm, the computation is reduced greatly, the core calculation process and matching process of algorithm are simplified, and the efficiency and precision is enhanced.
