Understanding the Jokes recommendation problem and the dataset

Dr. Ken Goldberg and his colleagues, Theresa Roeder, Dhruv Gupta, and Chris Perkins, introduced a dataset to the world through their paper Eigentaste: A Constant Time Collaborative Filtering Algorithm, which is pretty popular in the recommender-systems domain. The dataset is named the Jester's jokes dataset. To create it, a number of users are presented with several jokes and they are asked to rate them. The ratings provided by the users for the various jokes formed the dataset. The data in this dataset is collected between April 1999 and May 2003. The following are the attributes of the dataset:

  • Over 11,000,000 ratings of 150 jokes from 79,681 users
  • Each row is a user (Row ...

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