{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/using-posters-to-recommend-anime-and-mangas","title":"Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario","arxiv_id":"1709.01584","date":"2017-09-03","proceeding":null,"authors":["Jill-Jênn Vie","Florian Yger","Ryan Lahfa","Basile Clement","Kévin Cocchi","Thomas Chalumeau","Hisashi Kashima"],"abstract":"Item cold-start is a classical issue in recommender systems that affects\nanime and manga recommendations as well. This problem can be framed as follows:\nhow to predict whether a user will like a manga that received few ratings from\nthe community? Content-based techniques can alleviate this issue but require\nextra information, that is usually expensive to gather. In this paper, we use a\ndeep learning technique, Illustration2Vec, to easily extract tag information\nfrom the manga and anime posters (e.g., sword, or ponytail). We propose BALSE\n(Blended Alternate Least Squares with Explanation), a new model for\ncollaborative filtering, that benefits from this extra information to recommend\nmangas. We show, using real data from an online manga recommender system called\nMangaki, that our model improves substantially the quality of recommendations,\nespecially for less-known manga, and is able to provide an interpretation of\nthe taste of the users.","url_abs":"http://arxiv.org/abs/1709.01584v2","url_pdf":"http://arxiv.org/pdf/1709.01584v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"using-posters-to-recommend-anime-and-mangas","repo_url":"https://github.com/mangaki/balse","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"using-posters-to-recommend-anime-and-mangas","repo_url":"https://github.com/icyeyeball/Peitent","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}}],"tasks":[{"task_slug":"collaborative-filtering","task_name":"Collaborative Filtering"},{"task_slug":"recommendation-systems","task_name":"Recommendation Systems"},{"task_slug":"tag","task_name":"TAG"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}