The project objective is to build a hybrid recommendation engine by mixing recommendations from content-based filtering and collaborative filtering.
Recommendation systems have become an integral part of many businesses. They produce individualized recommendations as output or have the effect of guiding the user in a personalized way to interesting objects in a larger space of possible options.
The Dataset used for the project is https://www.kaggle.com/rounakbanik/the-movies-dataset. These files contain metadata for all 45,000 movies listed in the Full MovieLens Dataset.
Both content-based filtering and collaborative filtering have their strengths and weaknesses. We plan to mix both recommendations methods in addition to Graph Filter to provide a better personalized recommendation system.