Similarity of XML Schema Fragments Based on XML Data Statistics

As XML has become a standard for data representation, it can be found in plenty of information technologies. A possible optimization of XML-based approaches can be exploitation of similarity of XML data. In this paper we propose a technique for evaluating similarity of XML schema fragments focusing on two often omitted aspects - structural level of similarity and tuning of parameters of the similarity measure. In the former case we exploit the results of statistical analysis of real-world XML data. In the latter case we show that the tuning problem is a kind of constraints optimization problem and can be solved using corresponding approaches. We have analyzed (dis)advantages of two of them, genetic algorithms and simulated annealing, and in further experiments we show that appropriate tuning produces a more precise similarity measure.