Recommendation and ranking systems

Recommendation and ranking systems

• Movielens: Movie ratings dataset from the Movielens website, in various sizes ranging from demo to mid-size.
• Million Song Dataset: Large, metadata-rich, open source dataset on Kaggle that can be good for people experimenting with hybrid recommendation systems.
• Last.fm: Music recommendation dataset with access to underlying social network and other metadata that can be useful for hybrid systems.
• Book-Crossing dataset:: From the Book-Crossing community. Contains 278,858 users providing 1,149,780 ratings about 271,379 books.
• Jester: 4.1 million continuous ratings (-10.00 to +10.00) of 100 jokes from 73,421 users.
• Netflix Prize:: Netflix released an anonymized version of their movie rating dataset; it consists of 100 million ratings, done by 480,000 users who have rated between 1 and all of the 17,770 movies. First major Kaggle style data challenge. Only available unofficially, as privacy issues arose.