MultArtRec: A Multimodal Neural Topic Modeling for Integrating Image and Text Features in Artwork Recommendation
Jiayun Wang,
Akira Maeda,
Kyoji Kawagoe
Abstract:Recommender systems help users obtain the content they need from massive amounts of information. Artwork recommender systems is a topic that has attracted attention. However, existing art recommender systems rarely consider user preferences and multimodal information at the same time, while utilizing all the information has the potential to help make better personalized recommendations. To better apply recommender systems to the artwork-recommendation scenario, we propose a new neural topic modeling (NTM)-base… Show more
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