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dc.contributor.advisorTekinerdoğan, Bedir
dc.contributor.authorKalender, Mert Emin
dc.date.accessioned2016-01-08T18:28:13Z
dc.date.available2016-01-08T18:28:13Z
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/11693/15991
dc.descriptionAnkara : The Department of Computer Engineering and the Graduate School of Engineering and Science of Bilkent University, 2014.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2014.en_US
dc.descriptionIncludes bibliographical references leaves 79-82.en_US
dc.description.abstractThe scale of collaboration between people and computers has expanded leading to new era of computation called crowdsourcing. A variety of problems can be solved with this new approach by employing people to complete tasks that cannot be computerized. However, the existing approaches are focused on simplicity and independency of tasks that fall short to solve complex and sophisticated problems. We present Crowdy, a general-purpose and extensible crowdsourcing platform that lets users perform computations to solve complex problems using both computers and human workers. The platform is developed based on the stream-processing paradigm in which operators execute on the continuos stream of data elements. The proposed architecture provides a standard toolkit of operators for computation and configuration support to control and coordinate resources. There is no rigid structure or requirement that could limit the problem-set, which can be solved with the stream-based approach. The streambased human-computation approach is implemented and verified over different scenarios. Results show that sophisticated problems can be easily solved without significant amount of work for implementation. Also possible improvements are discussed and identified that is a promising future work for the existing work.en_US
dc.description.statementofresponsibilityKalender, Mert Eminen_US
dc.format.extentxii, 82 leaves, illustrations, graphicsen_US
dc.language.isoEnglishen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectCrowdsourcingen_US
dc.subjecthuman computationen_US
dc.subjectstream processingen_US
dc.subject.lccQA76.9.H84 K34 2014en_US
dc.subject.lcshCrowdsourcing.en_US
dc.subject.lcshHuman-computer interaction.en_US
dc.subject.lcshHuman computation.en_US
dc.titleCrowdy a framework for supporting socio-technical software : ecosystems with stream-based human computationen_US
dc.typeThesisen_US
dc.departmentDepartment of Computer Engineeringen_US
dc.publisherBilkent Universityen_US
dc.description.degreeM.S.en_US
dc.identifier.itemidB125351


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