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Collaborative Filtering Signal

Collaborative Filtering Signal

Collaborative filtering usually works by analyzing what many users like or dislike. However, building a full collaborative filtering system requires large amounts of user interaction data and complex calculations.
To keep the project simple and efficient, this system uses average movie ratings as a collaborative signal. These ratings represent how much users generally liked a movie.
Movies with higher average ratings are considered better choices. When multiple similar movies are found, the system gives more importance to movies that are highly rated. This helps ensure that the recommendations are not only similar in genre but also well-received by users.