Movie Recommender System using critic consensus
This is an incremental improvement for movie recommendation systems, potentially benefiting users and industry platforms.
The paper tackles the problem of disjointed collaborative and content-based filtering in movie recommendation systems by proposing a hybrid model that integrates user preferences with critic consensus scores, aiming to provide better recommendations.
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.