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Movie Recommender

A backend system that recommends movies to users based on Alternating Least Squares.

It is implemented in Scala by Manos Chatzakis, at EPFL ([email protected])

Functionalities

  • Data Loading: The system parses files of movies and ratings
  • Analytics: Provides basic analytics about the provided datasets
  • Aggregator: Provides aggregator functionalities about the movies and ratings. It also supports online data updates for the ratings
  • Recommender: Baseline and ALS-based recommendations

Movie Recommendations

Given a user and the preferred genres, the system predicts the ratings of the user for movies that match the genres using Alternating Least Squares, and returns the top predictions to the user.

Online Rating Updates

The system supports online rating updates. It calculates the updated rating of a movie using the formula

$$updatedRating = \frac{newRatingsSum + oldRatingsSum}{oldUsers+newUsers}$$

which is an optimized approach to calculate online ratings.

Spark Partitions

The system is designed for Spark. The default number for partitions is 8.

About

The system was implemented as part of the course "cs460: Systems for Data Management and Data science" of EPFL, during autumn semester of 2023.

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