【摘要】 为了更恰当地计算本体相似性,提出了一种本体的相似性网络推理的集成框架.该框架集成了基于外延的方法,基于内涵的方法,计算间接相似的相似性网络推理,和检验相似性测度有效性的环境反馈.同时,提出了一种用于构造概念相似性网络的新测度,相似性网络上的推理则采用图论实现而不是预定义知识规则,这样可免去知识获取的困难.框架已经应用于文本分类和高维数据的可视化,理论分析和实验验证了相似性网络推理框架的有效性.更多还原

【Abstract】 To properly compute the ontological similarity,an ontological similarity network-based reasoning framework is proposed.It structurally integrates extension-based approach,intension-based approach,the similarity network-based reasoning to exploit the implicit similarity,and the feedback from the context to validate the similarity measures.A new similarity measure is also presented to construct concept similarity network,which scales the similarity using the relative depth of the least common super-concept between any two concepts.Subsequently, the graph theory, instead of predefined knowledge rules, is applied to perform the similarity network-based reasoning such that the knowledge acquisition can be avoided.The framework has been applied to text categorization and visualization of high dimensional data.Theory analysis and the experimental results validate the proposed framework.更多还原