Application Research of Iterative Detection Strategy in the Crowdsourcing Quality Evaluation

DOI

10.2991/iset-15.2015.47How to use a DOI?

Keywords

Crowdsourcing, Quality control, Entropy, Iterative detection strategy, Quality evaluation

Abstract

Crowdsourcing appeared on the Internet as a new service mode. In order to improve the accuracy of crowdsourcing results evaluation, it presents a crowdsourcing iterative detection strategy. According to the task crowdsourcing workers complete, we can use the principle that the minority is subordinate to the majority to assess the results of the task. The result sets of the assessment task in which option is not unique will be regarded as a new task to release in the crowdsourcing platform. Candidate workers will be chosen to participate in the iterative detection operations until the optimal result of each task has been determined. Experimental results show that compared with the classic quality assessment algorithm based on entropy, this mechanism can achieve better results.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhiyun Zheng
AU  - Xiaoqiang Guo
AU  - Zhenfei Wang
AU  - Dun Li
AU  - Quanmin Li
PY  - 2015/03
DA  - 2015/03
TI  - Application Research of Iterative Detection Strategy in the Crowdsourcing Quality Evaluation
BT  - Proceedings of the First International Conference on Information Science and Electronic Technology
PB  - Atlantis Press
SP  - 186
EP  - 190
SN  - 2352-538X
UR  - https://doi.org/10.2991/iset-15.2015.47
DO  - 10.2991/iset-15.2015.47
ID  - Zheng2015/03
ER  -