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dc.contributor.authorBelhajjame, Khalid
dc.contributor.authorBrambilla, Marco
dc.contributor.authorGrigori, Daniela
dc.contributor.authorMauri, Andrea
dc.date.accessioned2017-09-14T08:27:39Z
dc.date.available2017-09-14T08:27:39Z
dc.date.issued2014
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/16699
dc.language.isoenen
dc.subjectcrowdsourcingen
dc.subjectKeyword searchen
dc.subjectKeyword search in Relational databasesen
dc.subjectMetadata searchen
dc.subject.ddc004en
dc.titleCommunity Profiling for Crowdsourcing Queriesen
dc.typeRapport
dc.description.abstractenCrowdsourcing has recently gained momentum as a means for outsourcing tasks to human workers with no specific expertise. This is a viable option for tasks that are difficult to achieve correctly using machines or that are too expensive to be carried out by expert professionals. This leads to the possibility of addressing large campaigns of jobs without facing extremely high cost. While this technique has proven to be effective for simple labeling tasks, such as text recognition, the quality of results it delivers for relatively sophisticated tasks such as scientific paper translation, may appear as deteriorated. The objective of our work is instead to define in a rich way the concept of community of workers, defining a way to properly match crowdsourcing tasks to the communities based on expertise of workers and field/topic of tasks. We describe a set of conceptual models for queries, communities and workers, a high level architecture of the approach, and outline a set of possible strategies for addressing various aspects of expert-targeted crowdsourcing.en
dc.relation.ispartofseriestitleCOST European cooperation in science and technologyen
dc.subject.ddclabelInformatique généraleen
dc.description.ssrncandidatenonen
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.description.rapportTypeRapport de rechercheen
dc.date.updated2017-09-14T08:12:40Z
hal.person.labIds989
hal.person.labIds20606
hal.person.labIds989
hal.person.labIds20606


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