Model Based Collaborative Recommender System by Integrating Word Embedding and Matrix Factorization
Eka Angga Laksana, Azizah Zakiah & Andry Septian Syahputra Tumaruk · Asian Journal of Research in Computer Science · 2026
Recommender systems assist users in identifying relevant products or services by predicting preferences from available interaction data. Collaborative filtering commonly relies on user-item ratings, while model-based approaches learn predictive representations from these ratings....
Open access
Research Article
10.9734/ajrcos/2026/v19i9909