  Recommendation systems are perhaps one of the most important agents for
industry growth through the modern Internet world. Previous approaches on
recommendation systems include collaborative filtering and content based
filtering recommendation systems. These 2 methods are disjointed in nature and
require the continuous storage of user preferences for a better recommendation.
To provide better integration of the two processes, we propose a hybrid
recommendation system based on the integration of collaborative and
content-based content, taking into account the top critic consensus and movie
rating score. We would like to present a novel model that recommends movies
based on the combination of user preferences and critical consensus scores.
