Author(s)

Shaorong Feng

Corresponding Author

Shaorong Feng

Abstract

In this paper, we propose a novel approach based on NSGA-II to address the problem of optimizing the aggregation of three different basic similarity measures (SyntacticMeasure, Linguistic Measure and Taxonomy-based Measure). Comparing with conventional genetic algorithm, the proposed method is able to realize three goals simultaneously, i.e. maximizing the alignment recall, the alignment precision and the f-measure, andthe resulted ontology alignment could avoid bias to recall or precision value. Experimental results show that the proposed approach is effective.

Keywords

Ontology, Alignment, NSGA-II, Aggregation of similarity measure