Classifying Personalities of Comic Characters Based on Egograms

Abstract

The aim of this research is to develop a search system for comics based on the personalities of appearing characters. For this purpose, this paper describes the classification of characters using egograms, which are used to classify personalities. In the proposed method, texts that express a comic book character's personality are acquired from web resources, and semantic vectors are allocated based on these texts using egograms. The resulting egogram pattern is used to estimate typical properties. Our experiment reveals that the performance accuracy of this classification method is 55.0%.

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