基于二部图模型的大本体分块与映射方法

针对当前大本体分块与映射方法中的块边界信息丢失严重、块间匹配计算复杂等问题，提出一种基于二部图模型的大本体分块与映射方法。根据本体概念相似度在2个本体间建立带权二部图模型，对该二部图进行分割，实现本体的关联分块，在子图中求解得到二部图的最佳匹配，并通过映射修正获得块内实体映射。实验结果表明，该方法的分块质量与映射效率均较优。

Large-scale Ontology Partition and Mapping Method Based on Bipartite Graph Model

Aiming at the defects of partition quality and mapping efficiency existed in large-scale ontology mapping, this paper proposes a new method for large-scale ontology partition and mapping based on bigraph graph model. A weighted bigraph is built by the similarity between the concepts of two ontologies and the bigraph is partitioned into subgraphs to achieve ontology co-partition. Then the ontology mapping problem is translated into an optimal matching problem in sub-graphs. It applies the revised rules to obtain alignments in the optimal matching. Experimental results show that partition quality and mapping efficiency of this method is well.