基于本体分割的本体映射算法

映射效率对于Web服务发现和组合、智能空间上下文感知等领域的动态映射至关重要。现有方法对相似度计算方法加以简化来提升效率，但当候选匹配实体对的数目随本体的规模增大而急剧增加时，就无法有效地处理。文中提出一种基于本体分割的高效本体映射算法。通过自下而上的聚类，将本体划分为一组大小合适的本体块。然后基于向量空间算法进行块映射，并从块映射结果中选取实体映射的候选匹配对，从而削减其数量，达到减少时间复杂度的目的。实验表明，文中方法显著提升运行时本体映射的效率，比Falcon-AO本体映射方法快6倍。

Ontology Mapping Method Based on Ontology Partition

The mapping efficiency is key to the performane of dynamic ontology mapping in Semantic Web Service descovery, context awareness in smart spaces and so on. The existing methods simplify the current methods of similarity computation to promotes the efficiency, nevertheless they fail in the case that the number of candidate mapping entity pairs increases when ontology gets larger. An efficient ontology mapping method based on ontology partition is proposed, which divides an ontology into a set of blocks through bottom up clustering. Then the blocks and candidate mapping entity pairs are mapped and selected from the block mapping result. The experimental results show that the proposed method promotes the efficiency of mapping significantly with 6 times faster than Falcon-AO.