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A Heterogeneous Information Network with an Attention Mechanism for Improving Recommender Systems
This manuscript introduces a novel attention-based recommender system that leverages heterogeneous information networks (HINs) to extract user and item representations and utilizes a matrix factorization framework to model interactions between users and items with the aim of predicting the ratings of users on items.
Narges Heidari, Parhamam Moradi
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