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Abstract : Matching crowd workers to suitable tasks is highly desirable as it can enhance task performance, reduce the cost for requesters, and increase worker satisfaction. In this paper, we propose a method that considers workers’ cognitive ability to predict their suitability for a wide range of crowdsourcing tasks. We measure cognitive ability via fast-paced online cognitive tests with a combined average duration of 6.2 min. We then demonstrate that our proposed method can effectively assign or recommend workers to five different popular crowd tasks: Classification, Counting, Proofreading, Sentiment Analysis, and Transcription. Using our approach we demonstrate a significant improvement in the expected overall task accuracy. While previous methods require access to worker history or demographics, our work offers a quick and accurate way to determine which workers are more suitable for which tasks.
https://hal.inria.fr/hal-02544572 Contributor : Hal IfipConnect in order to contact the contributor Submitted on : Thursday, April 16, 2020 - 2:30:13 PM Last modification on : Thursday, April 16, 2020 - 3:23:10 PM