Constarium
← Search

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.

Read the rest (1 more)

The archive is gzip compressed and includes 165,672 elections in PrefLib.org's TOC file format (Orders with Ties - Complete List).

Links

Topics

Stated by source
Economics and business

Related

Provenance · 1 source records, 9 field assertions
SourceKeyLast seenRaw
DataCite10.6084/m9.figshare.3972123.v111 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · DataCiteconnector:datacite@1.0.0/data/attributes/rightsList
byte_sizesource · DataCiteconnector:datacite@1.0.0
concepts[field].fos:economics-and-businesssource · DataCiteconnector:datacite@1.0.0
created_datesource · DataCiteconnector:datacite@1.0.0
descriptionsource · DataCiteconnector:datacite@1.0.0/data/attributes/descriptions
licensesource · DataCiteconnector:datacite@1.0.0/data/attributes/rightsList
publication_datesource · DataCiteconnector:datacite@1.0.0/data/attributes/dates
titlesource · DataCiteconnector:datacite@1.0.0/data/attributes/titles/0/title
updated_datesource · DataCiteconnector:datacite@1.0.0