Abstract: Recommender systems continuously strive to recommend items that the users potentially like accurately. Most recommender systems assume that latent user preferences and item features are ...
Abstract: Dear editor, This letter presents a novel multi-constrained matrix factorization (MMF) approach via the alternating-direction-method of multipliers (ADMM) for building a highly-accurate ...
A hybrid recommendation framework that integrates multi-matrix factorization and granular sentiment analysis to deliver explainable user-item matching. By jointly modeling user preferences and feature ...
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