Abstract: As an effective feature extraction and dimensionality reduction technique, nonnegative matrix factorization (NMF) has been widely applied in fault detection in recent years. The requirement ...

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 ...

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 ...