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Multi-attribute proportional representation
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DOI：10.1016/j.artint.2018.07.005.png)
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Abstract
En 中文
We consider the following problem in which a given number of items has to be chosen from a predefined set. Each item is described by a vector of attributes and for each attribute there is a desired distribution that the selected set should have. We look for a set that fits as much as possible the desired distributions on all attributes. An example of application is the choice of members for a representative committee, where candidates are described by attributes such as gender, age and profession, and where we look for a committee that for each attribute offers a certain representation, i.e., a single committee that contains a certain number of young and old people, certain number of men and women, certain number of people with different professions, etc. Another example of application is the selection of a common set of items to be used by a group of users, where items are labelled by attribute values. With a single attribute the problem collapses to the apportionment problem for party-list proportional representation systems (in such a case the value of the single attribute would be a political affiliation of a candidate). We study the properties of the associated subset selection rules, as well as their computational complexity. (C) 2018 Elsevier B.V. All rights reserved.
Keywords:
Proportional representation
Diversity
Multiwinner elections
Apportionment
Recommendation systems
Algorithms
Computational complexity
Approximation algorithms
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