Toward a movie recommender system based on association rules and LDA approach

With the growing amount of data on the web, it becomes very difficult for users to find the resources they are looking for. Recommender systems are used to solve the problem of information overload in order to offer the user more relevant resources.This work falls within the context of film recommender systems. We chose the area of movies because with the sky-rocketing rise of streaming platforms, more and more research is being conducted around recommending movies. There are several recommendation approaches, each with advantages and disadvantages. In our case, we realized a web platform named Movie Discovery which integrates two different recommendation techniques based on association rules and content-based filtering