摘要
针对传统基于特征的概念相似度计算方法准确性不高的问题,提出了基于FCA的概念相似度计算方法。该方法利用辞典形成两个本体特征之间的偏序关系,建立形式背景;以此为基础形成概念格。引入新的基于概念格的相似度计算模型,以概念格的不可约下确界元素作为相似度计算的依据。实验结果证明该方法提高了概念匹配的准确率。
In order to increase the precision of similarity computation based On traditional feature model, a new FCA-based concept similarity computational method is proposed. The attributes of classes in different ontologies is organized in a partial order set by means of a thesaurus, then the corresponding formal context and concept lattice is created. A new similarity computational model based on concept lattice is introduced, which allow us to compute concept similarity according to the meet-irreducible elements. The result of the experiment proves the FCA-based method can improve the precision of computation.
出处
《模糊系统与数学》
CSCD
北大核心
2008年第1期155-162,共8页
Fuzzy Systems and Mathematics
基金
国家自然科学基金资助项目(60172012)
武器装备预研基金资助项目(51421020904KG0135)
关键词
FCA
概念相似度
本体
Formal Concept Analysis
Concept Similarity
Ontology
