Abstract：The recent Risk Minimization based Ontology Mapping (RiMOM), based on multi-strategy, in spite of certain improvements, has the shortcomings in complexity and redundancy, and limitations in similarity selection of structure characteristics. Therefore, a comprehensive method of computing ontology similarity based on association rules was proposed. First, the "tree" model of association rules was constructed to compute the structure similarity. Then the similarity of instances, properties, and names were also computed. Finally, a comprehensive method was used to achieve the optimal calculation of the ontology similarity. The experimental results show that this method has higher recall and precision ratio and less time complexity than RiMOM.
李华 苏乐. 基于关联规则的本体相似度综合计算方法[J]. 计算机应用, 2012, 32(09): 2472-2475.
LI Hua SU Le. Comprehensive method of computing ontology similarity based on association rules. Journal of Computer Applications, 2012, 32(09): 2472-2475.
BELLAHSENE Z,BONIFATI A,RAHM E.Schema matching and mapping[M].Berlin:Springer-Verlag,2011:53-73.
[2]
RAHM E.Towards large-scale schema and ontology matching [C]// Proceedings of Schema Matching and Mapping (Data-Centric Systems and Applications).Berlin:Springer-Verlag,2011:3-27.
[3]
SHVAIKO P,EUZENAT J.Ten challenges for ontology matching[C]// Proceedings of the 2008 Conference on Ontologies,DataBases,and Applications of Semantics.Berlin:Springer-Verlag,2008:1163-1181.
LIJUANZI,TANG JIE,LI YI,et al.RiMOM:A dynamic multistrategy ontology alignment framework[J].IEEE Transactions on Knowledge and Data Engineering,2009,21(8):1218-1232.
[6]
VACCARI L,SHVAIKO P,PANE J,et al.An evaluation of ontology matching in geo-service applications[J].GeoInformatica,2012,16(1):31-66.
CHANGRUI,LIU ZHIYI.An improved Apriori algorithm[C]// Proceedings of 2011 International Conference on Electronics and Optoelectronics.Washington,DC:IEEE Computer Society,2011:476-478.
EUZENAT J,RHONE-ALPES I.Semantic precision and recall for ontology alignment evaluation[C]// Proceedings of the 20th International Joint Conference on Artificial Intelligence.San Francisco:[s.n.],2007:248-253.
2012, Vol. 32 
