• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science ›› 2010, Vol. 32 ›› Issue (5): 100-104.

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Causal Knowledge Extraction Based on Open Source Domain Texts

LI Yuequn,MAO Wenji,WANG Feiyue   

  1. (Key Laboratory of Complex Systems and Intelligence Science,
    Institute of Automation,Chinese Academy of Sciences,Beijing 100190,China)
  • Received:2009-11-15 Revised:2010-02-09 Online:2010-04-28 Published:2010-05-11
  • Contact: MAO Wenji E-mail:wenji.mao@ia.ac.cn

Abstract:

Causal knowledge is a kind of commonly used knowledge. It is also an important component of the domain knowledge base. The automatic extraction of causal knowledge based on the Web information resources is of great significance not only to the modeling of social computing systems,but the construction of intelligent systems as well. This paper aims at providing an automatic approach to causal knowledge extraction from open source Chinese texts of the security domain. Our approach can be applied to effectively support knowledge engineering on the Web, intelligence knowledge acquisition and automatic construction of the causal knowledge base.

Key words: open source information, knowledge extraction, causal relation

CLC Number: