Multi-labeled graph matching: an algorithm model for schema matching

Authors:
Zhi Zhang;Haoyang Che;Pengfei Shi;Yong Sun;Jun Gu
Affiliations:
Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China;Institute of Software, The Chinese Academy of Sciences, Beijing, China;Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China;Department of Computer Science, Science & Technology, University of Hong Kong, Hong Kong, China;Department of Computer Science, Science & Technology, University of Hong Kong, Hong Kong, China
Venue:
ASIAN'05 Proceedings of the 10th Asian Computing Science conference on Advances in computer science: data management on the web
Year:
2005

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Abstract

Schema matching is the task of finding semantic correspondences between elements of two schemas, which plays a key role in many database applications. In this paper, we treat the schema matching problem as a combinatorial problem. First, we propose an internal schema model, i.e., the multilabeled graph, and transform schemas into multi-labeled graphs. Secondly, we discuss a generic graph similarity measure, and propose an optimization function based on multi-labeled graph similarity. Then, we cast schema matching problem into a multi-labeled graph matching problem, which is a classic combinational problem. Finally, we implement a greedy algorithm to find the feasible matching results.