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About 05-UML Class Diagrams Similarity Aspects and Matching
The document discusses empirically validating the use of different metrics for capturing the similarity and differences between elements of two matched UML class diagrams. Compound metrics that combine individual metrics like name and neighborhood similarity showed more consistent matching performance across case studies than individual metrics alone. Calibrating the weights of compound metrics can improve matching accuracy by reducing the effect of less informative individual metrics.
Detailed Information
| Author: | ['Mohammad Nazir Arifin'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 7 |
| Language: | English |
| Format: | |
| Price: | FREE |
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