Computational social choice meets databases

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Abstract

We develop a novel framework that aims to create bridges between the computational social choice and the database management communities. This framework enriches the tasks currently supported in computational social choice with relational database context, thus making it possible to formulate sophisticated queries about voting rules, candidates, voters, issues, and positions. At the conceptual level, we give rigorous semantics to queries in this framework by introducing the notions of necessary answers and possible answers to queries. At the technical level, we embark on an investigation of the computational complexity of the necessary answers. In particular, we establish a number of results about the complexity of the necessary answers of conjunctive queries involving the plurality rule that contrast sharply with earlier results about the complexity of the necessary winners under the plurality rule.

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APA

Kimelfeld, B., Kolaitis, P. G., & Stoyanovich, J. (2018). Computational social choice meets databases. In IJCAI International Joint Conference on Artificial Intelligence (Vol. 2018-July, pp. 317–323). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2018/44

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