How Much Do Reviews Really Contribute? A Study on Text-Enriched Matrix Factorization for Recommendations (opens in new tab)

Incorporating textual reviews into a Recommender System has become a prominent strategy for enriching collaborative signals with semantic information. However, the actual contribution of review-derived representations remains an open question, particularly when strong collaborative baselines are employed. In this work, we systematically investigate the impact of textual information on Matrix Factorization by introducing and comparing three enric...