Heterogeneous fuzzy XML data integration based on structrual and semantic similarities | Amir Shokri
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 frame-work 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.
Keywords:
Heterogeneous data; Integration; Fuzzy XML; Structural similarity; Semantic similarity
Author:
Zongmin Ma a,∗, Zhen Zhao b, Li Yan a a College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu 211106, China b College of Information Science and Technology, Bohai University, Jinzhou, Liaoning 121013, China Received 23 February 2017; received in revised form 6 April 2018; accepted 30 April 2018
my work:
translate this article to persian(farsi)