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The purpose of the present study is to compare the cultures and social systems behind languages, based on probabilistic knowledge structures constructed from large scale language data in Japanese and Chinese. The present study applies the probabilistic algorithm developed by Kameya & Sato, more strict than the existing method like LSA (Latent Semantic Analysis). Practically, we compares interesting classes which have same names between Japanese and Chinese as the result of interpretation, selected from the latent classes estimated using the above algorithm. It is an important future plan to construct the same knowledge structures using other foreign languages like English. (受付日:2014 年 7 月 11 日,受理日:2014 年 10 月 22 日) 張 寓杰(チョウ ユージェー) 現職:東京工業大学大学院社会理工学研究科人間行動システム専攻 博士課程在学 首都大学東京大学教育センター 特任助教 2010 年首都師範大学(中国)教育研究科教育心理学専攻修士課程修了. 2011 年から東京工業大学大学院社会理工学研究科人間行動システム専攻博士課程在学. 現在は日本語と中国語の言語統計解析に基づく計算モデルを用いて,日本語と中国語における帰納的推 論の比較研究を行っている. 主な論文:張寓杰,寺井あすか,董媛,王月,中川正宣(2013). 日本語と中国語における帰納的推論の 比較研究―言語統計解析に基づく計算モデルを用いて―.「認知科学」,20(4), 439-469.

The comparative study of probabilistic knowledge structure between Japanese and Chinese