Similarity plays a crucial role in many research fields. Similarity serves as an organization principle by which individuals classify objects, form concepts. Similarity can be computed at different layers of abstraction: at data layer, at type layer or between the two layers (i.e. similarity between data and types). In this paper we propose an algorithm context path similarity, which captures the degree of similarity in the paths of two elements. In our approach, this similarity contributes to determine the structural similarity measure between XML schemas, in the domain of schema matching. We essentially focus on how to maximize the use of structural information to derive mappings between source and target XML schemas. For this, we adapt several existing algorithms in many fields, dynamic programming, data integration, and query answering to serve computing similarities.
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