计算机科学 ›› 2015, Vol. 42 ›› Issue (1): 276-278.doi: 10.11896/j.issn.1002-137X.2015.01.061

• 人工智能 • 上一篇    下一篇

不完备形式背景上的知识表示

智慧来   

  1. 河南理工大学计算机科学与技术学院 焦作454000
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金(60975033),河南理工大学博士基金(B2011-102)资助

Knowledge Representation on Incomplete Formal Context

ZHI Hui-lai   

  • Online:2018-11-14 Published:2018-11-14

摘要: 不完备形式背景中包含有不确定性信息,其上的知识表示与完备形式背景上的知识表示既有区别又有联系。为了研究两者的内在联系,定义了偏小近似形式背景与偏大近似形式背景,以及偏小近似概念格与偏大近似概念格,提出了偏大近似概念格上粗糙概念的识别方法,研究了偏小近似概念格与偏大近似概念格之间的蕴含关系。结论表明,可以用偏大近似概念格来作为不完备形式背景的知识表示工具。

关键词: 不完备形式背景,粗糙概念,精确概念,概念格

Abstract: Incomplete formal context contains uncertainty information,and thus knowledge representation on incomplete formal context and the one on complete formal context have distinction,and also have connection.In order to study their internal relationship,upper and lower approximate formal context,as well as upper and lower approximate concept lattice were defined respectively.Then a recognition method of rough concept was put forward.Moreover,the relationship between upper approximate concept lattice and lower approximate concept lattice was also studied.Conclusion shows that upper approximate concept lattice can be used as a knowledge representation tool for incomplete formal context.

Key words: Incomplete formal context,Rough concept,Exact concept,Concept lattice

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