Movie Recommendations with Spark Collaborative Filtering - KDnuggets

Collaborative filtering (CF) based on the alternating least squares (ALS) technique is another algorithm used to generate recommendations. It produces automatic predictions (filtering) about the interests of a user by collecting preferences from many other users (collaborating). The underlying assumption of the CF approach is that if a person A has the same opinion as a person B on an issue, A is more likely to have B's opinion on a different issue than a randomly chosen person. This algorithm gained a lot of traction in the data science community after it was used by the team winner of the Netflix Prize. The CF algorithm has also been implemented in Spark MLlib with the aim of addressing fast execution on very large datasets.