Skip to main content
Log in

Abstract

When evaluating the accessibility of a large website, we rely on sampling methods to reduce the cost of evaluation. This may lead to a biased evaluation when the distribution of checkpoint violations in a website is skewed and the selected samples do not provide a good representation of the entire website. To improve sampling quality, stratified sampling methods first cluster web pages in a site and then draw samples from each cluster. In existing stratified sampling methods, however, all the pages in a website need to be analyzed for clustering, causing huge I/O and computation costs. To address this issue, we propose a novel page sampling method based on URL clustering for web accessibility evaluation, namely URLSamp. Using only the URL information for stratified page sampling, URLSamp can efficiently scale to large websites. Meanwhile, by exploiting similarities in URL patterns, URLSamp cluster pages by their generating scripts and can thus effectively detect accessibility problems from web page templates. We use a data set of 45 web sites to validate our method. Experimental results show that our URLSamp method is both effective and efficient for web accessibility evaluation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  • Abou-Zahra, S., 2008. Web accessibility evaluation. In: Harper, S., Yesilada, Y. (Eds.), Web Accessibility: a Foundation for Research. Springer, London, p.79–106.

    Chapter  Google Scholar 

  • Astbrink, G., 2001. The legislative impact in Australia on universal access in telecommunications. Proc. Universal Access in Human-Computer Interaction Conf., p.1042–1046.

    Google Scholar 

  • Blanco, L., Dalvi, N., Machanavajjhala, A., 2011. Highly efficient algorithms for structural clustering of large websites. Proc. 20th Int. Conf. on World Wide Web, p.437–446. [doi:10.1145/1963405.1963468]

    Chapter  Google Scholar 

  • Brajnik, G., 2006. An Accessibility Evaluation Method Based on Barrier Walkthrough. Available from http://www.dimi.uniud.it/giorgio/projects/bw.

    Google Scholar 

  • Brajnik, G., 2008. A comparative test of web accessibility evaluation methods. Proc. 10th Int. ACM SIGACCESS Conf. on Computers and Accessibility, p.113–120. [doi:10.1145/1414471.1414494]

    Google Scholar 

  • Brajnik, G., Lomuscio, R., 2007. SAMBA: a semi-automatic method for measuring barriers of accessibility. Proc. 9th Int. ACM SIGACCESS Conf. on Computers and Accessibility, p.43–50. [doi:10.1145/1296843.1296853]

    Chapter  Google Scholar 

  • Brajnik, G., Mulas, A., Pitton, C., 2007. Effects of sampling methods on web accessibility evaluations. Proc. 9th Int. ACM SIGACCESS Conf. on Computers and Accessibility, p.59–66. [doi:10.1145/1296843.1296855]

    Chapter  Google Scholar 

  • Disability Rights Commission, 2004a. Formal Investigation Report: Web Accessibility.

    Google Scholar 

  • Disability Rights Commission, 2004b. The Web: Access and Inclusion for Disabled People-a Formal Investigation. The Stationery Office, UK.

    Google Scholar 

  • Ellison, J., 2004. Assessing the accessibility of fifty United States government web pages: using Bobby to check on Uncle Sam. First Monday, 9(7). [doi:10.5210/fm.v9i7.1161]

    Google Scholar 

  • Hanson, V.L., Richards, J.T., 2004. A web accessibility service: update and findings. Proc. 6th Int. ACM SIGACCESS Conf. on Computers and Accessibility, p.169–176. [doi:10.1145/1028630.1028661]

    Google Scholar 

  • Hanson, V.L., Richards, J.T., 2013. Progress on website accessibility. ACM Trans. Web, 7(1), Article 2. [doi:10.1145/2435215.2435217]

    Article  Google Scholar 

  • Henzinger, M.R., Heydon, A., Mitzenmacher, M., et al., 2000. On near-uniform URL sampling. Comput. Netw., 33(1–6): 295–308. [doi:10.1016/S1389-1286(00)00055-4]

    Article  Google Scholar 

  • Hong, S., Katerattanakul, P., Joo, S.J., 2008. Evaluating government website accessibility: a comparative study. Int. J. Inform. Technol. Dec. Mak., 7(3):491–515. [doi:10.1142/S0219622008003058]

    Article  Google Scholar 

  • Kawanaka, S., Borodin, Y., Bigham, J.P., et al., 2008. Accessibility commons: a metadata infrastructure for web accessibility. Proc. 10th Int. ACM SIGACCESS Conf. on Computers and Accessibility, p.153–160. [doi:10.1145/1414471.1414500]

    Google Scholar 

  • King, M., Thatcher, J.W., Bronstad, P.M., et al., 2005. Managing usability for people with disabilities in a large web presence. IBM Syst. J., 44(3):519–535. [doi:10.1147/sj.443.0519]

    Article  Google Scholar 

  • Mankoff, J., Fait, H., Tran, T., 2005. Is your web page accessible?: a comparative study of methods for assessing web page accessibility for the blind. Proc. SIGCHI Conf. on Human Factors in Computing Systems, p.41–50. [doi:10.1145/1054972.1054979]

    Google Scholar 

  • Marincu, C., McMullin, B., 2004. A comparative assessment of web accessibility and technical standards conformance in four EU states. First Monday, 9(7). [doi:10.5210/fm.v9i7.1160]

    Google Scholar 

  • Pernice, K., Nielsen, J., 2001a. Beyond ALT Text: Making the Web Easy to Use for Users with Disabilities. Technical Report, Nielsen Norman Group, USA.

    Google Scholar 

  • Pernice, K., Nielsen, J., 2001b. How to Conduct Usability Studies for Accessibility. Technical Report, Nielsen Norman Group, USA.

    Google Scholar 

  • Rusmevichientong, P., Pennock, D.M., Lawrence, S., et al., 2001. Methods for sampling pages uniformly from the World Wide Web. Proc. AAAI Fall Symp. on Using Uncertainty within Computation, p.121–128.

    Google Scholar 

  • Sullivan, T., Matson, R., 2000. Barriers to use: usability and content accessibility on the web’s most popular sites. Proc. ACM Conf. on Universal Usability, p.139–144. [doi:10.1145/355460.355549]

    Google Scholar 

  • Ulltveit-Moe, N., Snaprud, M., Nietzio, A., et al., 2006. Early Results from Automatic Accessibility Benchmarking of Public European Web Sites from the European Internet Accessibility Observatory (EIAO). Available from http://mortengoodwin.net/publicationfiles/dfa2006.pdf.

    Google Scholar 

  • Velleman, E., Velasco, C., Snaprud, M., et al., 2006. DWAB4 Unified Web Evaluation Methodology (UWEM 1.0). Technical Report, WAB Cluster.

    Google Scholar 

  • Vigo, M., Brajnik, G., 2011. Automatic web accessibility metrics: where we are and where we can go. Interact. Comput., 23(2):137–155. [doi: 10.1016/j.intcom.2011.01.001]

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Can Wang.

Additional information

Project supported by the National Natural Science Foundation of China (Nos. 61173185 and 61173186) and the Natural Science Foundation of Zhejiang Province, China (No. LZ13F020001)

ORCID: Meng-ni ZHANG, http://orcid.org/0000-0002-7547-0168; Can WANG, http://orcid.org/0000-0002-5890-4307

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Mn., Wang, C., Bu, Jj. et al. A sampling method based on URL clustering for fast web accessibility evaluation. Frontiers Inf Technol Electronic Eng 16, 449–456 (2015). https://doi.org/10.1631/FITEE.1400377

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1631/FITEE.1400377

Key words

CLC number

Navigation