会议论文详细信息
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
来源: CEUR
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【 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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