An ontology algorithm based on iterated Laplacian semi-supervised learning
Banghuang Peng · Computer Engineering and Science · 2014
Ontology similarity measure and ontology mapping are central contexts for knowledge representation and information processing.An ontology algorithm based on iterated Laplacian semi-supervised learning is proposed.Using iterated Laplacian semi-supervised learning method,all the vertices of the ontology graph are mapped into real numbers.Then,the ontology similarity measure algorithm and the ontology mapping strategy are obtained by comparing the differences of their corresponding values.Two experiments confirm that the new algorithm has high quality for special application fields.