Heterogeneous fuzzy XML data integration based on structural and semantic similarities

Abstract

Web data integration has become a crucial requirement for Web data management. A considerable number of approaches for integrating Extensible Markup Language (XML) data from heterogeneous data sources have been proposed. Yet these existing approaches are not fit for integration of fuzzy XML data because of their fuzzy characteristics. In this article, we provide a framework to deal with fuzzy XML document integration. Firstly, we propose a new fuzzy XML tree model. Secondly, we present an effective algorithm based on the tree edit distance to identify the structural and semantic similarities between the fuzzy documents represented in the proposed fuzzy XML tree model. Thirdly, we propose an integration strategy that is applied to integrate the fuzzy documents from different data sources. Finally, we conduct experiments to demonstrate that our approach can efficiently integrate fuzzy XML documents.