计算机应用 ›› 2012, Vol. 32 ›› Issue (11): 3009-3013.DOI: 10.3724/SP.J.1087.2012.03009

• 人工智能 • 上一篇    下一篇

领域知识语义距离及其在专家系统中的应用

李建勋1,2,沈冰2,解建仓2,姜仁贵2   

  1. 1. 西安理工大学 经济与管理学院,西安 710048
    2. 西安理工大学 水利水电学院,西安 710048
  • 收稿日期:2012-05-13 修回日期:2012-07-05 发布日期:2012-11-12 出版日期:2012-11-01
  • 通讯作者: 李建勋
  • 作者简介:李建勋(1977-),男,陕西乾县人,讲师,博士研究生,CCF会员,主要研究方向:知识发现、专家系统;沈冰(1948-),男,浙江湖州人,教授,博士,主要研究方向: GIS、旱区水文过程及水资源演变;解建仓(1963-),男,陕西眉县人,教授,博士,主要研究方向:决策支持系统、水资源管理;姜仁贵(1985-),男,江西玉山人,博士研究生,CCF会员,主要研究方向:水文学及水资源。
  • 基金资助:
    国家自然科学基金资助项目(11102124);国家863项目(2006AA01A126);教育部人文社会科学研究青年基金资助项目(10XJCZH002)

Domain knowledge semantic distance and its application in expert system

LI Jian-xun1,2,SHEN Bing2,XIE Jian-cang2,JIANG Ren-gui2   

  1. 1. Faculty of Economics and Management, Xi’an University of Technology, Xi’an Shaanxi 710048,China
    2. Faculty of Water Resources and Hydraulic Power, Xi’an University of Technology, Xi’an Shaanxi 710048,China
  • Received:2012-05-13 Revised:2012-07-05 Online:2012-11-12 Published:2012-11-01
  • Contact: LI Jian-xun
  • Supported by:
    ;National High-Tech Research and Development Plan of China

摘要: 面向专家系统中的可程序化知识间距离的测度,在构造领域知识本体及本体树的基础上,建立知识身份距离、知识概念距离、知识属性距离、知识描述距离四个测度,并在规范化后采用有序加权几何算子对其加以集结,形成一个更加全面且应用性强的领域知识语义距离模型,有效地解决了专家系统中领域知识的判别问题。实验表明:该模型可快速地判别专家系统中两领域知识的相似程度,并具有82%以上的评判正确率。

关键词: 领域知识本体, 领域知识语义距离, 专家系统

Abstract: Oriented to the measurement of programmable knowledge distance in the expert system, based on the domain knowledge ontology and ontology tree, the paper established four measurements: knowledge identity distance, knowledge concept distance, knowledge attribute distance, and knowledge description distance, which were assembled by Ordered Weighted Geometric (OWG) operator after being standardized. As a result, a more comprehensive domain knowledge semantic distance model with strong applicability was obtained, so as to effectively solve the identification problem of domain knowledge database in expert system. The results show that: this model can quickly determine the similarity of two domain knowledge in expert system with an accuracy of above 82%.

Key words: domain knowledge ontology, domain knowledge semantic distance, expert system

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