[3J1-GS-6a] 言語メディア処理：基礎

[3J1-GS-6a-03] Relative risk between situations

Comprehensive analysis of situations based on distributed representation

〇Masaaki Ozaki¹, Emiko Uchiyama¹, Yoshifumi Nishida¹ (1. Tokyo Institute of Technology)

Keywords:Big data, Risk analysis, Epidemiological analysis, Text mining, Injury prevention

In this paper, we propose a new method for situational relative risk analysis that integrates a natural language processing technique and an epidemiological basic indicator, relative risk. The free-description style text data for accident situations were divided into 2 parts; pre- and post-accidental situation and converted into the situation vectors using distributed representation. For each part of the text data, the relative risk for situations was calculated. The relationship between the relative risk of the 2 parts was analyzed. To verify our method, we used the disaster benefit system of the Japan Sport Council (JSC) that is the complete data of school accidents in Japan. The proposed method enabled us to analyze the changes of the relative risk with the situation changes and to extract dangerous combinations of pre- and post-accidental situations.