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Computational Social Choice in the Clouds

dc.contributor.authorCsar, Theresa
dc.contributor.authorLackner, Martin
dc.contributor.authorPichler, Reinhard
dc.contributor.authorSallinger, Emanuel
dc.contributor.editorMitschang, Bernhard
dc.contributor.editorNicklas, Daniela
dc.contributor.editorLeymann, Frank
dc.contributor.editorSchöning, Harald
dc.contributor.editorHerschel, Melanie
dc.contributor.editorTeubner, Jens
dc.contributor.editorHärder, Theo
dc.contributor.editorKopp, Oliver
dc.contributor.editorWieland, Matthias
dc.date.accessioned2017-06-21T11:24:37Z
dc.date.available2017-06-21T11:24:37Z
dc.date.issued2017
dc.description.abstractIn the era of big data we are concerned with solving computational problems on huge datasets. To handle huge datasets in cloud systems dedicated programming frameworks are used, among which MapReduce is the most widely employed. It is an important issue in many application areas to design parallel algorithms which can be executed efficiently on cloud systems and can cope with big data. In computational social choice we are concerned with computational questions of joint decision making based on preference data. The question of how to handle huge preference datasets has not yet received much attention. In this report we summarize our recent work on designing and evaluating algorithms for winner determination in huge elections using the MapReduce framework.en
dc.identifier.isbn978-3-88579-660-2
dc.identifier.pissn1617-5468
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-266
dc.subjectComputational Social Choice
dc.subjectCloud Computing
dc.subjectMapReduce
dc.subjectParallel Computing
dc.subjectDis- tributed Computing
dc.titleComputational Social Choice in the Cloudsen
dc.typeText/Conference Paper
gi.citation.endPage168
gi.citation.publisherPlaceBonn
gi.citation.startPage163
gi.conference.date6.-10. März 2017
gi.conference.locationStuttgart
gi.conference.sessiontitleWorkshop Präferenzen und Personalisierung in der Informatik (PPI17)

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