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PREDICTING FUTURE PERFORMANCE OF MULTIPLE WORKERS ON CROWDSOURCING TASKS AND SELECTING REPEATED CROWDSOURCING WORKERS
PREDICTING FUTURE PERFORMANCE OF MULTIPLE WORKERS ON CROWDSOURCING TASKS AND SELECTING REPEATED CROWDSOURCING WORKERS
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机译:预测多名工人在众包任务上的未来表现并选择重复的众包工人
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摘要
Systems and methods of a job distribution platform for aggregating performance data in a worker profile for workers in performing crowd sourced tasks are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of generating and storing performance data when a worker performs one or more tasks distributed online to their respective computing devices by a job distribution platform which crowd sources tasks over a network to remote workers. The tasks can span current jobs and a history of previous jobs distributed to the worker and the job performance data for the worker is collected for current and previous jobs. New jobs can be assigned to a worker selected based on performance data of the worker. Other types of worker information may also be tracked and generated for multiple workers in various worker pools (channels), for example, psych questions or other more subjective data collected from a worker or contributor in addition to performance.
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