Manga Scene Estimation by Quiz and Answer

In reading manga, it is common to look back at the storyline when following a serialized work. Although there are services that assist comic re-reading through quizzes, searching for specific parts related to the quiz takes a lot of time and complicates the review process. Therefore, in this study, we examined whether it is possible to estimate the scenes related to the quiz based on the quiz questions, answers, and manga-specific features. To achieve this, we extracted key elements from the comic and proposed two estimation methods: a word-based CS method and a context-based GPT method. Furthermore, we discussed extractable and difficult-to-estimate scenes in comics. The results showed that the pages containing the answers could be estimated with a probability of 66.7%. Pages containing specific keywords or events were easier to estimate, while those requiring an understanding of the comic’s overall time series and context were more difficult to estimate. In addition, since the accuracy varied greatly depending on the presence or absence of the answer text, it can be considered that the content as close as possible to the topic of the quiz can be estimated if important keywords such as the answer text are included.