PrefLib
PrefLib is a reference library of preference data and links assembled by Nicholas Mattei, Toby Walsh and lately Simon Rey. This site and library is proudly supported by the Algorithmic Decision Theory group at Data61 and the The COMSOC Group at the University of Amsterdam.
We want to provide a comprehensive resource for the multiple research communities that deal with preferences, including computational social choice, recommender systems, data mining, machine learning, and combinatorial optimization, to name just a few.
For more information on PrefLib and some helpful tips on using it, please see Nick's Tutorial Slides and Code from EXPLORE 2014. Check out the data type page to learn more about the kind of data we provide.
Please see the about page for information about the site, contacting us, and our citation policy. We rely on the support of the community in order to grow the usefulness of this site. To contribute, please contact Nicholas Mattei at: nsmattei{at}gmail or Simon Rey at: s.j.rey{at}uva{dot}nl.
MD-00001-00000145.wmd from the Kidney Data dataset
In Brief
We currently host:
- 11 types of data
- 38 datasets
- 3668 data files
- More than 3.37 Gb. of data
Other Links
Here are some links that you might find relevant as well.
- DEMOCRATIX: A Declarative Approach to Winner Determination
- Pnyx: An Easy to Use Aggregation Tool
- Whale4: Which Alternative is Elected?
- VoteLib: A Library of Voting Behavior
- Pabulib: A Library of Participatory Budgeting Instances
- CRISNER: A Qualitative Preference Reasoner
- Spliddit: Quick and Easy Solutions to Fair Division Problems
- RoboVote: AI Driven Decisions
To find more data check these websites.
- UC Irvine Machine Learning Repository
- University of Minnesota GroupLens Data Sets
- CSPLib: A Problem Library for Constraints
- Microsoft Learning to Rank Datasets
- SATLib: The Satisfiability Library
- Preference-Learning.org
- Toshihiro Kamishima's Sushi Preference Dataset
- MAX-SAT Evaluations and Datasets
- Stanford Network Analysis Project