计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (21): 96-98.DOI: 10.3778/j.issn.1002-8331.2008.21.026

• 机器学习 • 上一篇    下一篇

认知学习中的知识约等价问题

樊建聪1,梁永全1,唐雷雨2,阮久宏3   

  1. 1.山东科技大学 信息科学与工程学院,山东 青岛 266510
    2.山东科技大学 理学院,山东 青岛 266510
    3.山东交通学院 科研处,济南 250023
  • 收稿日期:2008-04-30 修回日期:2008-05-26 出版日期:2008-07-21 发布日期:2008-07-21
  • 通讯作者: 樊建聪

Equivalence and approximate equivalence problem in cognitive learning

FAN Jian-cong1,LIANG Yong-quan1,TANG Lei-yu2,RUAN Jiu-hong3   

  1. 1.College of Information Science and Engineering,Shandong University of Science and Technology,Qingdao,Shandong 266510,China
    2.College of Science,Shandong University of Science and Technology,Qingdao,Shandong 266510,China
    3.Scientific Research Department,Shandong Jiaotong University,Ji’nan 250023,China
  • Received:2008-04-30 Revised:2008-05-26 Online:2008-07-21 Published:2008-07-21
  • Contact: FAN Jian-cong

摘要: 人类的知识获取过程通常是利用已有知识来推知相关知识的过程,机器学习可以借助这一过程,从学习的逆过程出发,把知识作为学习的出发点,来对认知学习进行研究和应用。以已有的知识作为参照知识,经过等价变换或约等价变换,产生新的知识。约等价变换过程包括知识的约等价扩充和约等价约简。等价变换过程处理同一层次的知识,约等价扩充过程产生细节级知识,约等价约简过程产生抽象级知识。实例分析表明,采用知识的约等价扩充和约简算法所产生的新知识的准确率较高,能够产生当前已有知识的细节级和抽象级新知识,为认知机器学习的知识处理提供了一定参考。

关键词: 认知, 机器学习, 等价, 约等价, 约简

Abstract: The knowledge acquisition of mankind usually takes advantage of the known knowledge to infer relevant unknown knowledge.Machine learning can resort to mankind’s process of knowledge acquisition.From the reverse process of learning,knowledge can be viewed as the start point of the learning processing to study and apply the results of cognitive learning.The known knowledge regarded as referential knowledge produces new knowledge through equivalent and approximate equivalent transformation.Approximate equivalent transformation includes expanding process and reduction process.Equivalent transformation processes knowledge of the same hierarchies.Expanding process of approximate equivalence produces detailed-level knowledge,and reduction process produces abstract-level knowledge.Instances analysis show that expanding and reduction algorithms have high accuracy for inferring new knowledge and can produce detailed and abstract level knowledge.

Key words: cognition, machine learning, equivalence, approximate equivalence, reduction