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- W1592644486 abstract "One relevant issue in metamodel matching is how to select the most suitable matching technique to execute for a given couple of metamodels, and how to adjust parameters (e.g., threshold, F-measure, quality). In this paper, we present a flexible method for selecting the most appropriate metamodel matching technique for a given couple of metamodels. The proposed method assists the user to choose the most suitable matching technique that provides good quality of matches. This method relies on a new quality metric called Score and, on using a decision tree. In order to validate our method, we conduct experimental results on ten real-world metamodels and four recent matching techniques." @default.
- W1592644486 created "2016-06-24" @default.
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- W1592644486 date "2014-01-01" @default.
- W1592644486 modified "2023-09-25" @default.
- W1592644486 title "A New Flexible Method for Advising Metamodel Matching" @default.
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- W1592644486 doi "https://doi.org/10.5220/0004714903760383" @default.
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