A Multilayer Method of Schema Matching Based on Semantic and Functional Dependencies

Determing matching schemas enables queries on heterogeneous data space to be formulated and facilitates data integration. Current schema matching techniques most focus on mining mappings using elements´ own information. This paper proposes to introduce semantic and functional dependencies into matching process to achieve multilayer schema matching results. It calculates semantic similarity with the help of Word Net and generates candidate mapping sets. By introducing functional dependency to formulize structural information, it can get structural similarities between element pairs. A probabilistic factor is considered to select mapping pairs. Through experimental evaluation on real data, the superiority of our method is verified.