基于层次本体模型(HOM)的语义相似度计算方法

Ontology alignment establishes the relation between entities by computing their semantic similarities using the local or/and global context of entities. Besides the local and global context of entities, the relations between two ontologies are helpful for computing their semantic similarity in many situations. The aim of this article is to improve the performance of ontology alignment by using these relations in similarity computing. A hierarchical ontology model (HOM) which is based on category theory and describes these relations formally is proposed followed by HOM-matching, an algorithm based on HOM. It makes use of the relations between ontologies to compute semantic similarity. Two groups of experiments are conducted for algorithm validation and parameters optimization.