Abstract
We show a prototype of a system that uses multiwinner voting to suggest resources (such as movies) related to a given query set (such as a movie that one enjoys). Depending on the voting rule used, the system can either provide resources very closely related to the query set or a broader spectrum of options. We show how this ability can be interpreted as a way of controlling the diversity of the results. We test our system both on synthetic data and on the real-life collection of movie ratings from the MovieLens dataset. We also present a visual comparison of the search results corresponding to selected diversity levels.
Connections
Explore this paper’s authors, topics and related work.
Building this map preview
BZPEER is loading the nearby papers, people, topics and institutions for this page.
Reviews 0
Write a review
No reviews yet.
Discussion 0
Add a comment
No comments yet.