Extending the method for schema matching by adding support for additional data types and taking the structure of the schema into account

摘要

Schema matching aims at identifying semantically similar elements of two schemas and determining the mappings between them. This process is one of the main activities in data integration. Most of the existing methods for finding mappings between schemas still have difficulties with complex mappings. Therefore, we decided to improve one of the existing methods which deals primarily with finding complex mappings. The chosen method in based on an evolutionary algorithm that generates progressively better individuals (mappings) only on the basis of data instances. It may happen that in a certain scenario the data instances are not available. That is why we have developed an improved method which also takes the schema data into consideration. We have further improved the chosen method by adding support for additional data types. Our improved method was evaluated on the same test data as the original method. We have found that our method is 20 % more accurate on average than the original one for both simple and complex mappings.