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IEICE Transactions on Information and Systems 2008 E91-D(4):959-968; doi:10.1093/ietisy/e91-d.4.959
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Copyright © 2008 The Institute of Electronics, Information and Communication Engineers

Special Section on Knowledge-Based Software Engineering -- Papers -- Knowledge Engineering

Cause Information Extraction from Financial Articles Concerning Business Performance

Hiroyuki SAKAI1 and Shigeru MASUYAMA1

1 The authors are with the Department of Knowledge-based Information Engineering, Toyohashi University of Technology, Toyohashi-shi, 441–8580 Japan. E-mail: sakai{at}smlab.tutkie.tut.ac.jp; masuyama{at}tutkie.tut.ac.jp


  Abstract

We propose a method of extracting cause information from Japanese financial articles concerning business performance. Our method acquires cause information, e.g. "[See PDF] (zidousya no uriage ga koutyou: Sales of cars were good)". Cause information is useful for investors in selecting companies to invest. Our method extracts cause information as a form of causal expression by using statistical information and initial clue expressions automatically. Our method can extract causal expressions without predetermined patterns or complex rules given by hand, and is expected to be applied to other tasks for acquiring phrases that have a particular meaning not limited to cause information. We compared our method with our previous one originally proposed for extracting phrases concerning traffic accident causes and experimental results showed that our new method outperforms our previous one.

Key Words: cause information, causal expression, knowledge extraction, information extraction

Manuscript received July 2, 2007. Manuscript revised October 17, 2007.


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