A mediator is a software component that helps accessing data sources. With the advent of the Web, the design of mediators imposes important challenges, such as the ability of providing integrated access to independent and dynamic data sources and the ability of resolving the semantic heterogeneity between different data source schemas. To deal with these challenges, schema matching is a fundamental issue. In this thesis, matching approaches for classification schemas (thesauri) and conceptual schemas are proposed, using instances as evidences for the mappings. The proposed approaches are classified as adaptative and a priori, referring to, respectively, the discovery of the mappings in an incremental way or the definition of the mappings before the deployment of the mediator. Finally, experiments to validate and test the proposed approaches are presented.