[3G1] [General Session] 9. NLP / IR

[3G1-03] Extraction of rare cause-result expressions from summary of financial statements

〇Hiroyuki Sakai¹, Hiroki Sakaji², Risa Murono¹, Ryozo Kitajima¹, Jason Bennett³ (1. Seikei University, 2. The University of Tokyo, 3. Sumitomo Mitsui Asset Management Company, Limited)

Keywords:Text mining, Summary of financial statements, Cause-result expressions

In this research, we propose a method to extract rare cause-result expressions from summary of financial statements. For example, our method extracts effect expression that "Sales of drinking paper containers has increased" with respect to cause expression that "due to hot summer", as a rare cause-result expression. It is difficult to imagine that the sales of “drinking paper containers” may increase in the case of “hot summer”. Our method calculates the conditional probability with words contained in the result expression co-occurring with words contained in the cause expressions. Moreover, our method determines that cause information is contained in the result expression or not by using deep learning. Our method extracts rare cause-effect expressions by using the conditional probability and the cause information.