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计算机工程 ›› 2009, Vol. 35 ›› Issue (2): 184-186. doi: 10.3969/j.issn.1000-3428.2009.02.065

• 人工智能及识别技术 • 上一篇    下一篇

模糊Horn子句规则及其发现算法

刘东波1,2,卢正鼎1   

  1. (1. 华中科技大学计算机科学与技术学院,武汉 430074;2. 中国电子设备系统工程研究所,北京 100039)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-01-20 发布日期:2009-01-20

Fuzzy Horn Clause Rules and Its Discovery Algorithm

LIU Dong-bo1,2, LU Zheng-ding1   

  1. (1. College of Computer Science & Technology, Huazhong University of Science & Technology, Wuhan 430074; 2. Institute of China Electronic System Engineering, Beijing 100039)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-01-20 Published:2009-01-20

摘要: 模糊Horn子句规则可以用自然语言来表达人类知识。但是,发现模糊Horn子句规则及其蕴含度是比较困难的。该文从逻辑的观点出发,定义模糊Horn子句规则、支持度、蕴含度及其相关概念,分析模糊Horn子句规则发现的步骤,并给出发现算法的形式化描述。该算法结合了模糊Horn子句逻辑概念和Apriori发现算法,从给定的数量型数据库中发现模糊Horn子句规则。

关键词: 模糊Horn子句规则, 支持度, 蕴含度, 定量数据库

Abstract: Fuzzy Horn clause rules can be used to represent human knowledge in terms of natural language. However, it is more difficult to discover fuzzy Horn clause rules and its implication degree. From the logical point of view, in this paper, fuzzy Horn clause rules, support degree, implication degree and related concepts are defined. The processes of mining fuzzy Horn clause rules are analyzed, and the formal algorithm is proposed. This algorithm integrates the concepts of fuzzy Horn clause logic and the Apriori algorithm to find fuzzy Horn clause rules from quantitative databases.

Key words: fuzzy Horn clause rules, support degree, implication degree, quantitative databases

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