Development of the method of extracting causal expressions from Japanese financial articles concerning business performance and analyzing them for supporting decision on investment

我们开发了一种方法，从涉及公司经营业绩的日本金融文章中提取因果表达式，并自动赋予它们重要性。被赋予重要性的因果表达式对于投资者在选择要投资的公司、业务预测和技术趋势预测时很有用。我们的方法通过使用统计信息和初始线索表达式自动提取因果信息作为因果表达式的形式。我们从这些公司的网站中提取了关键词，并利用它们对以前的方法进行了改进。此外，我们的方法通过从公司的网站中提取关键字来自动确定最重要的因果表达式，我们对该方法进行了评估，得到了77个。3%的准确率，实验结果表明，我们的方法优于LEAD(S2)方法和LEAD(CE)方法，LEAD(S2)方法将关于公司经营业绩的文章中出现的第二个句子确定为最重要的因果表达式，而LEAD(CE)方法将首先从关于公司经营业绩的文章中提取的因果表达式确定为最重要的因果表达式。

We have developed a method of extracting causal expressions from Japanese financial articles concerning business performance of companies and assigning importance to them automatically. Causal expressions assigned importance are useful for investors in selecting companies to invest, business prediction, and technology-trends prediction. Our method automatically extracted causal information as a form of causal expression by using statistical information and initial clue expressions. We extracted keywords from Web sites of the companies and improved the previous method by using them. Moreover, our method automatically determined the most important causal expression by using these keywords extracted from Web sites of the companies.We evaluated our method and it attained 77. 3% accuracy and the experimental results showed that our method outperforms Lead(s2) method which determines the sentence which appears in the 2nd in an article concerning business performance of companies as the most important causal expression and Lead(ce) method which determines a causal expression first extracted from an article concerning business performance of companies as the most important causal expression.