摘要
映射效率对于动态映射的应用至关重要,因此文中提出基于模块化的大规模本体映射方法.通过加权的基于距离和基于信息量的方法计算本体概念的相似度,利用改进的凝聚层次聚类算法对概念进行聚类,并以此抽取子本体,最后设计基于信息检索的技术发现异构本体中的相关子本体.该方法有效缩小候选匹配的搜索空间,达到减少时间复杂度的目的.实验表明,文中方法可在保证映射结果质量的同时提升映射效率.
The mapping efficiency is the key to some dynamic mapping applications. A modularization based large-scale ontology mapping approach is proposed. Firstly, it uses a weighted semantic distance and information content based method is employed to calculate the similarity of ontology concepts. Then, by an improved efficient agglomerative hierarchical clustering algorithm, the concepts are clustered and the sub-ontologies are extracted. Finally, an elaborate information retrieval based method is designed to find related sub-ontologies from heterogeneous ontologies. The proposed approach reduces time complexity by pruning candidate search space effectively. The experimental results show that the proposed approach improves the mapping efficiency significantly with high-quality mapping results.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2016年第5期410-416,共7页
Pattern Recognition and Artificial Intelligence
关键词
本体映射
本体模块化
凝聚层次聚类
信息检索
Ontology Mapping, Ontology Modularization, Agglomerative Hierarchical Clustering,Information Retrieval
