Learning from Sets of Items in Recommender Systems

no code implementations • 22 Apr 2019 • Mohit Sharma, F. Maxwell Harper, George Karypis

Our analysis of these ratings shows that though the majority of the users provide the average of the ratings on a set's constituent items as the rating on the set, there exists a significant number of users that tend to consistently either under- or over-rate the sets.

Collaborative Filtering Recommendation Systems