Adaptive Similarity of XML Data

In the present work we explore application of XML schema mapping in conceptual modeling of XML schemas. We expand upon the previous efforts to map XML schemas to PIM schema via a decision tree. In this thesis more versatile method is implemented - the decision tree is trained from a large set of user- annotated mapping decision samples. Several variations of training that could improve the mapping results are proposed. The approach is evaluated in a wide range of experiments that show the advantages and disadvantages of the proposed variations of training. The work also contains a survey of different approaches to schema mapping and description of schema used in this work. Powered by TCPDF (www.tcpdf.org