Abstract
Crowdsourcing technology can help manual testing by soliciting the contributions from volunteer evaluators. But crowd evaluators may give inaccurate or invalid evaluation results. This paper proposes an advanced crowdsourcing-based web accessibility evaluation system called CrowdAE by enhancing the crowdsourcing-based manual testing module of the previous version. Through three main process namely learning system, task assignment and task review, we can improve the quality of evaluation results from the crowd. From the comparison on the two years’ evaluation process of Chinese government websites, our CrowdAE outperforms the previous version and improve the accuracy of the evaluation results.
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Acknowledgement
This work is supported by the National Natural Science Foundation of China (Nos. 61173185 and 61173186), the National Key Technology R&D Program of China (No. 2012BAI34B01 and 2014BAK15B02), and the Hangzhou S&T Development Plan (No. 20150834M22).
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Li, L. et al. (2018). CrowdAE: A Crowdsourcing System with Human Inspection Quality Enhancement for Web Accessibility Evaluation. In: Miesenberger, K., Kouroupetroglou, G. (eds) Computers Helping People with Special Needs. ICCHP 2018. Lecture Notes in Computer Science(), vol 10896. Springer, Cham. https://doi.org/10.1007/978-3-319-94277-3_5
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DOI: https://doi.org/10.1007/978-3-319-94277-3_5
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