Probabilistic Topic Model for Hybrid Recommender Systems: A Stochastic Variational Bayesian Approach
Internet recommender systems are popular in contexts that include heterogeneous consumers and numerous products. In such contexts, product features that adequately describe all the products are often not readily available. Content-based systems therefore rely on user-generated content such as product reviews or textual product tags to make recommendations.