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2014 International Conference on Big Data and Smart Computing (BIGCOMP) (2014)
Bangkok, Thailand
Jan. 15, 2014 to Jan. 17, 2014
ISBN: 978-1-4799-3919-0
pp: 60-65
Sooyoung Lee , Dept. of Computer Science and Engineering, Sogang University, Seoul, Korea
Sehwa Park , Dept. of Computer Science and Engineering, Sogang University, Seoul, Korea
Seog Park , Dept. of Computer Science Engineering, Sogang University, Seoul, Korea
ABSTRACT
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 always ensure the precision of the results, which are generated by unspecified individuals. In particular, a more sophisticated task has more complex problems that are related to the accuracy of the result. In this paper, we propose a novel framework to improve the quality of work in a crowdsourcing environment. In this framework, we analyzes the characteristics of workers and allocates the appropriate task to individuals to improve the quality of work. It also provides cumulative voting for correct assessment instead of the majority representation method, which is more commonly used. Our experiments show that this framework facilitates effective work allocation.
INDEX TERMS
Quality Analysis, Crowdsourcing, Task Distribution
CITATION

Sooyoung Lee, Sehwa Park and Seog Park, "A quality enhancement of crowdsourcing based on quality evaluation and user-level task assignment framework," 2014 International Conference on Big Data and Smart Computing (BIGCOMP), Bangkok, Thailand, 2014, pp. 60-65.
doi:10.1109/BIGCOMP.2014.6741408
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