Movie Recommender System

Version: Spark – 2.2.1, Python – 2.7

Command to run on terminal:

spark-submit [CF python file] [input file] [testing file]

The above command will generate an output file in the current directory

• Implementation of User-User, Item-Item and Model Collaborative Filtering methods on the MovieLens Database.
• Locality Sensitive Hashing was used to speed up computation of Item-Item pairs
• Item-Item performs best with lowest RMSE of 0.94

Approximate running times:

• User-user: 600s
• Item-item (with LSH): 400s
• Model based: 14s

Note: testing file must be a subset of input file and both should resemble the ratings.csv file on MovieLens Database