Abstract—In this paper, we propose a method to extract foreigner interests for Japanese culture from interactive digital contents, making use of quick exchange trait of instant messages (IM) on Social Network Service (SNS). It is difficult for foreigners who living in Japan to know their interest about Japanese culture because of language barrier and cultural differences. The method enables them to search how to enjoy Japanese culture based on their interests. From the experiment, we found that people from the same country tend to be more interested in the same topics. The result indicates we can provide excitements for foreigners from a specific country, preparing appropriate topics for individual countries in advance. It implies we can develop an automatic consultation system to introduce traditional Japanese culture to foreigners.
Index Terms—Data mining, extract topic, machine learning, Naïve Bayes classifiers.
T. N. Le is with Ritsumeikan University, Shiga, 5258577 Japan (e-mail: le@de.is.ritsumei.ac.jp).
H. Shimakawa is with the Data Engineering Lab, Ritsumeikan University, Shiga, 5258577 Japan (e-mail: simakawa@cs.ritsumei.ac.jp).
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Cite:Thi Ngoc Le and Hiromitsu Shimakawa, "Extracting Foreigner Interests for Japanese Culture from Interactive Digital Contents," International Journal of Information and Electronics Engineering vol. 7, no. 3, pp. 108-112, 2017.
