Kim, JaewookPeng, YunIvezik, NenadShin, Junho2018-11-262018-11-262011-01-30Jaewook Kim, Yun Peng, Nenad Ivezik, and Junho Shin, An Optimization Approach for Semantic-based XML Schema Matching, International Journal of Trade, Economics, and Finance, 2011, https://ebiquity.umbc.edu/paper/html/id/600/An-Optimization-Approach-for-Semantic-based-XML-Schema-Matchinghttp://hdl.handle.net/11603/12088We propose a novel solution for semantic-based XML schema matching, taking a mathematical programming approach. This method identifies the globally optimal solution for the problem of matching leaf nodes between two XML schema trees by reducing the tree-to-tree matching problem to simpler problems of path-to-path, node-to-node, and word-to-word matching. We formulate these matching problems as maximum-weighted bipartite graph matching problems with different constraints, which are solved by different mathematical programming techniques, including integer programming and dynamic programming. Solutions to simpler problems provide weights for the next stage until the optimal tree-to-tree matching solution is obtained. The effectiveness of this approach has been verified and demonstrated by computer experiments.9 pagesen-USThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.Public Domain Mark 1.0This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.E-businessXML schema matchingmaximum-weighted bipartite graphsemantic similaritymathematical programmingUMBC Ebiquity Research GroupText