首页> 外文会议>Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on >Knowledge reasoning and Tableau Algorithm improving based on rough description logics
【24h】

Knowledge reasoning and Tableau Algorithm improving based on rough description logics

机译:基于粗糙描述逻辑的知识推理和Tableau算法的改进

获取原文

摘要

The knowledge base of description logics are composed of two parts TBox and ABox. Tableau Algorithm is for the uniformity testing in the knowledge reasoning of DLs, which is based on two-value logics, it can not realize the uniformity testing for multiple-valued concepts. This paper take the fundamental ideal to the system of DLs, improving Tableau Algorithm through the definition of rough concept implication degree, and by using rough concept express related concepts and relationships in the TBbox, The rough description logics can be completed on the reasoning of rough concept, laying the foundation for knowledge base inference engine design.
机译:描述逻辑的知识库由TBox和ABox两部分组成。 Tableau算法是基于二值逻辑的DL知识推理中的一致性测试,无法实现多值概念的一致性测试。本文以DLs系统的基本理想为基础,通过定义粗糙概念的蕴涵度,改进Tableau算法,并通过在TBbox中使用粗糙概念表达相关的概念和关系,可以在粗糙推理的基础上完成粗糙描述逻辑。概念,为知识库推理机设计奠定基础。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号