Computer Engineering and Applications ›› 2006, Vol. 42 ›› Issue (1): 17-19.

• 博士论坛 • Previous Articles     Next Articles

Causality Automaton Based on Knowledge Discovery

Bingru Yang,xin li,Weidong Li,Kejun Zhang   

  1. 北京科技大学 信息工程学院
  • Received:2005-10-19 Revised:1900-01-01 Online:2006-01-01 Published:2006-01-01
  • Contact: xin li

基于知识发现的因果自动机

杨炳儒,李欣,李卫东,张克君   

  1. 北京科技大学 信息工程学院
  • 通讯作者: 李欣 tj_lixin tj_lixin

Abstract: With the development of society, people's study on causality is being paid attention to, but up till now have all been basically look for causality from existing knowledge, the unable defect of finding deeper relation and law exists. For this reason, we utilize the finite automaton characteristics to portray the behaviors of the software system or their subsystems accurately, proceed with finite automaton, use the method of knowledge discovery, excavate out deeper causality and law to the question that need solving, combine the theory of knowledge discovery with the research of causality organically, form the theory and method of causality more systematically, set up the state space of cause and effect, form the preliminary theory frame of causality automaton based on knowledge discovery, in order to solve and find the causality under different shapes.

Key words: causality, state space of cause and effect, causality automaton, knowledge discovery

摘要: 随着社会的发展,人们对因果关系的研究越来越被重视,但到目前为止基本都是从现有的知识中寻找因果关系,存在无法发现更深层次的关系和规律的缺陷。为此,我们利用有限自动机可以精确地刻画软件系统或其子系统的行为的特性,从有限自动机入手,运用知识发现的方法,针对需要解决的问题挖掘出更深层次的因果关系和规律,将知识发现理论与因果关系的研究有机结合,较系统地形成因果关系的理论和方法,建立因果状态空间,形成基于知识发现的因果自动机的初步理论框架,以解决和发现不同形态下的因果关系。

关键词: 因果关系, 因果状态空间, 因果自动机, 知识发现