@inproceedings{688208463dfd4f86a0cd000268200b74,
title = "Achieving fully proportional representation by clustering voters",
abstract = "Both the Chamberlin-Courant and Monroe rules are voting rules solving the problem of so-called fully proportional representation: they select committees whose members represent the voters so that voters' satisfaction with their assigned representatives is maximized. These rules suffer from a common disadvantage, being that it is computationally intractable to compute the winning committee exactly. As both of these rules, explicitly or implicitly, partition voters, they can be seen as clustering the voters so that the voters in each group share the same representative. This suggests studying approximation algorithms for these voting rules by means of cluster analysis, which is the subject of this paper. We develop several algorithms based on clustering the voters and analyze their performance experimentally.",
keywords = "Clustering, Multiwinner elections, Voting",
author = "Piotr Faliszewski and Arkadii Slinko and Kolja Stahl and Nimrod Talmon",
note = "Publisher Copyright: Copyright {\textcopyright} 2016, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.; 15th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2016 ; Conference date: 09-05-2016 Through 13-05-2016",
year = "2016",
month = jan,
day = "1",
language = "American English",
series = "Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS",
pages = "296--304",
booktitle = "AAMAS 2016 - Proceedings of the 2016 International Conference on Autonomous Agents and Multiagent Systems",
}