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|Author(s):||Jaewook Kim; Yun Peng; Nenad Ivezic; Jun H. Shin;|
|Title:||Semantic-based Optimal XML Schema Matching: A Mathematical Programming Approach|
|Published:||February 09, 2011|
|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 two XML schemas 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.|
|Proceedings:||2010 International Conference on E-business, Management and Economics|
|Location:||Hong Kong, -1|
|Dates:||December 28-30, 2010|
|Keywords:||E-business, XML schema matching, optimization, maximum weighted bipartite graph, semantic similarity, integer programming, dynamic programming|
|Research Areas:||Supply Chain|
|PDF version:||Click here to retrieve PDF version of paper (413KB)|