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 multi-labeled 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.
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Zhang, Z., Che, H., Shi, P., Sun, Y., Gu, J. (2005). Multi-labeled Graph Matching – An algorithm Model for Schema Matching. In: Grumbach, S., Sui, L., Vianu, V. (eds) Advances in Computer Science – ASIAN 2005. Data Management on the Web. ASIAN 2005. Lecture Notes in Computer Science, vol 3818. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11596370_9
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DOI: https://doi.org/10.1007/11596370_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30767-9
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