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JBE, vol. 23, no. 1, pp.53-62, January, 2018
Helper Classification via Three Dimensional Visualization of Character-net
Seung-Bo Park, Yoon Bae Jeon, Juhyun Park, and Eun Soon You
C.A E-mail: firstname.lastname@example.org
It is necessary to analyze the character that are a key element of the story in order to analyze the story. Current character analysis methods such as Character-net and RoleNet are not sufficient to classify the roles of supporting characters by only analyzing the results of the final accumulated stories. It is necessary to study the time series analysis method according to the story progress in order to analyze the role of supporting characters rather than the accumulated story analysis method. In this paper, we propose a method to classify helpers as a mentor and a best friend through 3-D visualization of Character-net and evaluate the accuracy of the method. WebGL is used to configure the interface for 3D visualization so that anyone can see the results on the web browser. It is also proposed that rules to distinguish mentors and best friends and evaluated their performance. The results of the evaluation of 10 characters selected for 7 films confirms that they are 90% accurate.
Keyword: Character-net, visualization, helper classification, mentor, best friend
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