1st International Workshop on Nature Inspired Reasoning for the Semantic Web | |
Optimizing Ontology Alignments by Using Genetic Algorithms | |
计算机科学;图书情报档案学 | |
Jorge Martinez-Gil ; Enrique Alba ; José F. Aldana-Montes | |
Others : http://CEUR-WS.org/Vol-419/paper2.pdf PID : 24999 |
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来源: CEUR | |
【 摘 要 】
In this work we present GOAL (Genetics for Ontology Alignments) a new approach to compute the optimal ontology alignment function for a given ontology input set. Although this problem could be solved by an exhaustive search when the number of similarity measures is low, our method is expected to scale better for a high number of measures. Our approach is a genetic algorithm which is able to work with several goals: maximizing the alignment precision, maximizing the alignment recall, maximizing the f-measure or reducing the number of false positives. Moreover, we test it here by combining some cutting-edge similarity measures over a standard benchmark, and the results obtained show several advantages in relation to other techniques.
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Files | Size | Format | View |
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Optimizing Ontology Alignments by Using Genetic Algorithms | 474KB | download |