model-based

Collaborative filtering (CF) is a technique that can filter out items that a user might like based on the behaviors and preferences of similar users.  It is a key en-abler technique for an effective recommendation system (RS).  Model-based recommendation systems, a subset of CF, use data, typically ratings, to construct models for providing personalized suggestions to users.  Our objective in this work is to provide a comprehensive overview of various techniques employed in Model-based RS, focusing on their theoretical foundations and practical applications.  We explore