Comics is usually classified into broad categories called “genres” according to its contents such as comedy, horror, science fiction, etc. Because a genre expresses a comics story briefly, people read comics which has contents based on their interest, by relying on comics genres. However, giving only one genre to one comic cannot express the detailed difference of the story. In this paper, we propose a system for generating comics story representation as a sub-sequence of genres. Our comics story representation can be applied to a new search engine based on stories or to a recommendation system which analyzes the tastes of the user’s favorite comics by finding comics with similar story representation. We use a deep neural network to classify each page into the corresponding genre. Experimental results confirm the advantage of the proposed system.
Export this publication
Tab-separated. Paste into the sheet starting at column A. Required fields that cannot be inferred are left blank.
Format definition
Edits apply immediately and stay in effect until you pick a style again or reset. First line is the default; add lines like "book: …" to override per type.
How to write the definition
Insert a field with braces like {authors}. A part enclosed in [ ... ] is omitted entirely when any field inside it is empty. Available fields:
One macro per line as \name{field}{field}…. A field name in braces is replaced by its (LaTeX-escaped) value; other text is kept. Rename macros or add lines freely — they appear in the macro selector. A line like master_thesis: thesis fixes the macro for a type (automatic choice: journals use paperdoi with a DOI, paperno with a number, else paper; conferences conf with pages, else confpaper; books book). {pages} comes as 119--124; {journal} falls back to the book title. Fields: