摘要
对两个及以上的相关领域本体进行合并,使用基于形式概念分析方法可以方便有效地合并本体。但是它并没有按照用户对一些属性的特殊需求和喜好而进行本体的合并。针对这个问题提出了一种基于熵和偏差的加权概念格的本体合并方法来满足上述需求,同时通过实验给出了方法中的阈值D(B)的量化公式。
For two or more related ontology merging, the usage of methods based on FCA（formal concept analysis） can easily and effectively merge the ontologies. But it does not follow some attributes of the specific user needs and preferences for ontology merging. To deal with the problem, an ontology merging method based on information entropy and deviation is proposed to meet these needs. Through large experiments, we have given threshold D（B） quantitative formula.
出处
《计算机与数字工程》
2014年第5期760-765,882,共7页
Computer & Digital Engineering
关键词
本体合并
形式背景
加权概念格
信息熵
差分分析
ontology merging, formal context, weighted concept lattice, information entropy, deviation analysis
