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Crowdsourcing ontology engineering

Crowdsourcing ontology engineering. Elena Simperl Web and Internet Science, University of Southampton 11 April 2013. Overview. "online, distributed problem-solving and production model“ [ Brabham , 2008]

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Crowdsourcing ontology engineering

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  1. Crowdsourcing ontology engineering Elena Simperl Web and Internet Science, University of Southampton 11 April 2013

  2. Overview • "online, distributed problem-solving and production model“ [Brabham, 2008] • Varieties: wisdom of the crowds/collective intelligence, open innovation, human computation... • Why is it a good idea? • Cost and efficiency savings • Wider acceptance, closer to user needs, diversity • Approaches • Collaborative ontology engineering • Challenges/competitions • Games with a purpose • Microtask/paid crowdsourcing • In combination with automatic techniques

  3. Crowdsourcing ontology alignment • Experiments usingMTurk, CrowdFlowerandestablishedbenchmarks • Enhancingtheresultsofautomatictechniques • Fast, accurate, cost-effective [Sarasua, Simperl, Noy, ISWC2012]

  4. Open questions • Quality assurance and evaluation • Incentives and motivators • Choice of crowdsourcing approach and combinations of different approaches • Reusable collection of algorithms for quality assurance, task assignment, workflow management, results consolidation etc • Schemas recording provenance of crowdsourced data • Descriptive framework for classification of human computation systems • Typesoftasksandtheirmodeofexecution • Participantsandtheirroles • Interaction withsystemandamongparticipants • Validation ofresults • Consolidationandaggregationofinputsintocompletesolution

  5. Theory and practice of social machineswww.sociam.org http://sociam.org/www2013/

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