Movie Recommender System using critic consensus

TL;DR

This paper introduces a hybrid movie recommender system that combines user preferences with critic consensus scores to improve recommendation accuracy, addressing limitations of traditional collaborative and content-based methods.

Contribution

A novel hybrid model integrating collaborative filtering, content-based filtering, and critic consensus scores for enhanced movie recommendations.

Findings

Improved recommendation accuracy over traditional methods

Effective integration of critic consensus with user preferences

Potential for better personalized movie suggestions

Abstract

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.