Abstract
Schema matching, the problem of finding semantic correspondences between elements of source and warehouse schemas, plays a key role in data warehousing. Currently, the mappings are largely determined manually by domain experts, thus a time-consuming process. In this paper, based on a multistrategy schema matching framework, we develop a linguistic matching algorithm using semantic distances between words to compute their semantic similarity, and propose a structural matching algorithm based on semantic similarity propagation. After describe our approach, we present experimental results on several real-world domains, and show that the algorithm discovers semantic mappings with a high degree of accuracy.
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Cheng, W., Lin, H., Sun, Y. (2005). An Efficient Schema Matching Algorithm. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552451_134
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DOI: https://doi.org/10.1007/11552451_134
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28895-4
Online ISBN: 978-3-540-31986-3
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