Data · dataset · 2016
Netflix Prize Data: 5 candidate elections with weak preferences
Listed in DataCite
The Netflix Prize was a competition devised by Netflix to improve the accuracy of its recommendation system.
Description
To facilitate this Netflix released real ratings about movies from the users (voters) of the system. Any set of movies can be transformed into an election via a process outlined by Mattei, Forshee, and Goldsmith.
This data set includes all 5 candidate elections with at least 350 voters generated by this process from 300 randomly chosen movies. Extending beyond prior work by Mattei et al. we allow for weak preferences, i.e., a voter is indifferent between a set of movies if he assigns the same rating to each of them. Thus, there are 541 possibilities to rank a given set of five movies.
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The archive is gzip compressed and includes 165,672 elections in PrefLib.org's TOC file format (Orders with Ties - Complete List).
Links
Where it is published
- Repository landing page figshare.com/articles/dataset/Netflix_Prize_Data_5_candidate_elections_with… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.3972123 ↗
DOI / persistent id · from DataCite
Documentation and papers
- Creative Commons Zero v1.0 Universal creativecommons.org/publicdomain/zero/1.0/legalcode ↗
license · from DataCite
Catalogue records · 2
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.3972123 ↗
metadata API · from DataCite
- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.3972123 ↗
catalogue entry · from DataCite
Topics
- Stated by source
- Economics and business
Related
- Inverse of same asNetflix Prize Data: 5 candidate elections with weak preferences
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.3972123 | 11 d ago | JSON v1 |
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| updated_date | source · DataCite | connector:datacite@1.0.0 |