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T. Csar, M. Lackner, R. Pichler, E. Sallinger:
"Winner Determination in Huge Elections with MapReduce";
Talk: 10th Multidisciplinary Workshop on Advances in Preference Handling, New York City, USA; 2016-07-09; in: "10th Multidisciplinary Workshop on Advances in Preference Handling", M. Endres, N. Mattei, A. Pfandler (ed.); (2016), 7 pages.

In computational social choice, we are concerned with the development of methods for joint decision making. A central problem in this field is the winner determination problem, which aims at identifying the most preferred alternative(s). With the rise of modern e-business platforms, processing of huge amounts of preference data has become an issue. In this work, we apply the MapReduce framework - which has been specifically designed for dealing with big data - to various versions of the winner determination problem. Our main result are efficient and highly parallel algorithms together with a performance analysis for this problem.

Project Head Reinhard Pichler:
Effiziente, parametrisierte Algorithmen in Künstlicher Intelligenz und logischem Schließen

Project Head Reinhard Pichler:
Heterogene Information Integration

Project Head Reinhard Pichler:
SEE: SPARQL Evaluation and Extensions

Project Head Stefan Woltran:
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