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A Quality Enhancement of Crowdsourcing based on Quality Evaluation and User-Level Task Assignment Framework |
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PP: 423-430 |
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Author(s) |
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Sooyoung Lee,
Kangsoo Jung,
Seog Park,
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Abstract |
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| Crowdsourcing has recently been used in various applications, and the possibility of its utilization and importance is
expected to increase continuously in the future. However, crowdsourcing cannot ensure the precision of the results because it is
performed by unspecified individuals who cannot guarantee the quality of results. In particular, a more sophisticated task that has
complex problems is harder to get an accurate result. In this paper, we propose a novel framework to improve the quality of work in
a crowdsourcing environment. We analyze the characteristics of workers and allocate the appropriate task to workers to improve the
quality of results. We propose a cumulative voting for correct assessment instead of the majority representation method which is more
commonly used. Our experiments show that proposed framework improves quality of results by effective work allocation and quality
analysis. |
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