Structural and semantic aspects of similarity of Document Type Definitions and XML schemas

The natural optimization strategy for XML-to-relational mapping methods is exploitation of similarity of XML data. However, none of the current similarity evaluation approaches is suitable for this purpose. While the key emphasis is currently put on semantic similarity of XML data, the main aspect of XML-to-relational mapping methods is analysis of their structure. In this paper we propose an approach that utilizes a verified strategy for structural similarity evaluation - tree edit distance - to DTD constructs. This approach is able to cope with the fact that DTDs involve several types of nodes and can form general graphs. In addition, it is optimized for the specific features of XML data and, if required, it enables one to exploit the semantics of element/attribute names. Using a set of experiments we show the impact of these extensions on similarity evaluation. And, finally, we discuss how this approach can be extended for XSDs, which involve plenty of ''syntactic sugar'', i.e. constructs that are structurally or semantically equivalent.