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An optimal sampling method for web accessibility quantitative metric and its online extension
Abstract
Purpose
As existing studies show the accuracy of sampling methods depends heavily on the evaluation metric in web accessibility evaluation, the purpose of this paper is to propose a sampling method OPS-WAQM optimized for Web Accessibility Quantitative Metric (WAQM). Furthermore, to support quick accessibility evaluation or real-time website accessibility monitoring, the authors also provide online extension for the sampling method.
Design/methodology/approach
In the OPS-WAQM method, the authors propose a minimal sampling error model for WAQM and use a greedy algorithm to approximately solve the optimization problem to determine the sample numbers in different layers. To make OPS-WAQM online, the authors apply the sampling in crawling strategy.
Findings
The sampling method OPS-WAQM and its online extension can both achieve good sampling quality by choosing the optimal sample numbers in different layers. Moreover, the online extension can also support quick accessibility evaluation by sampling and evaluating the pages in crawling.
Originality/value
To the best of the authors’ knowledge, the sampling method OPS-WAQM in this paper is the first attempt to optimize for a specific evaluation metric. Meanwhile, the online extension not only greatly reduces the serious I/O issues in existing web accessibility evaluation, but also supports quick web accessibility evaluation by sampling in crawling.
Keywords
Acknowledgements
This work is supported by Zhejiang Provincial Natural Science Foundation of China (Grant No. LZ13F020001) and National Science Foundation of China (Grant Nos 61173185, 61173186), and National Key Technology R&D Program (Grant No. 2012BAI34B01).
Citation
Zhang, M.,Wang, C.,Bu, J.,Li, L. andYu, Z. (2017), "An optimal sampling method for web accessibility quantitative metric and its online extension",Internet Research, Vol. 27 No. 5, pp. 1190-1208.https://doi.org/10.1108/IntR-07-2016-0205
Publisher
:Emerald Publishing Limited
Copyright© 2017, Emerald Publishing Limited