Abstract—We 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.
Index Terms—E-business, XML schema matching,
maximum-weighted bipartite graph, semantic similarity,
mathematical programming.
Jaewook Kim is with the Department of Computer Science and Electrical
Engineering, University of Maryland, Baltimore County, Baltimore, MD
21250 USA (e-mail: jaewook2@umbc.edu).
Yun Peng is with the Department of Computer Science and Electrical
Engineering, University of Maryland, Baltimore County, Baltimore, MD
21250 USA (e-mail: ypeng@umbc.edu).
Nenad Ivezic is with the National Institute of Standards and Technology,
Gaithersburg, MD 20899 USA (e-mail: nivezic@nist.gov).
Junho Shin is with the National Institute of Standards and Technology,
Gaithersburg, MD 20899 USA (e-mail: junho.shin@nist.gov).
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Cite:Jaewook Kim, Yun Peng, Nenad Ivezic, and Junho Shin, "An Optimization Approach for Semantic-based XML Schema Matching," International Journal of Trade, Economics and Finance vol.2, no.1, pp. 78-86, 2011.