Abstract: To overcome the drawback that an entire standard ontology alignment must be provided beforehand in current evolutionary-algorithm-based ontology matching technologies, we propose an ontology matching approachbased on local standard ontology alignment. First, we utilize the ontology concept of the clustering algorithm to build the local standard ontology alignment, and then construct a multi-object optimization model for the ontology matching problem based on the local standard ontology alignment. Then, we propose a multiobjective evolutionary algorithm based on decomposition (MOEA/D) that is also based on the local standard ontology alignment. We conducted an experiment using a testing dataset from the ontology alignment evaluation initiative 2012, and the results demonstrate the effectiveness of the proposed approach.