A sampling method based on URL clustering for fast web accessibility evaluation

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.

Keywords

Page sampling / URL clustering / Web accessibility evaluation

References

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

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

[3] 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. [

[4] Brajnik, G., 2006. An Accessibility Evaluation Method Based on Barrier Walkthrough. Available from

[5] Brajnik, G., 2008. A comparative test of web accessibility evaluation methods. Proc. 10th Int. ACM SIGACCESS Conf. on Computers and Accessibility, p.113-120. [

[6] 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. [

[7] 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. [

[8] Disability Rights Commission, 2004a. Formal Investigation Report: Web Accessibility.

[9] Disability Rights Commission, 2004b. The Web: Access and Inclusion for Disabled People—a Formal Investigation. The Stationery Office, UK.

[10] Ellison, J., 2004. Assessing the accessibility of fifty United States government web pages: using Bobby to check on Uncle Sam. First Monday, 9(7). [

[11] 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. [

[12] Hanson, V.L., Richards, J.T., 2013. Progress on website accessibility. ACM Trans. Web, 7(1), Article 2. [

[13] Henzinger, M.R., Heydon, A., Mitzenmacher, M., , 2000. On near-uniform URL sampling. Comput. Netw., 33(1-6): 295-308. [

[14] 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. [

[15] Kawanaka, S., Borodin, Y., Bigham, J.P., , 2008. Accessibility commons: a metadata infrastructure for web accessibility. Proc. 10th Int. ACM SIGACCESS Conf. on Computers and Accessibility, p.153-160. [

[16] King, M., Thatcher, J.W., Bronstad, P.M., , 2005. Managing usability for people with disabilities in a large web presence. IBM Syst. J., 44(3): 519-535. [

[17] 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. [

[18] Marincu, C., McMullin, B., 2004. A comparative assessment of web accessibility and technical standards conformance in four EU states. First Monday, 9(7). [

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

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

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

[22] 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. [

[23] Ulltveit-Moe, N., Snaprud, M., Nietzio, A., , 2006. Early Results from Automatic Accessibility Benchmarking of Public European Web Sites from the European Internet Accessibility Observatory (EIAO). Available from

[24] Velleman, E., Velasco, C., Snaprud, M., , 2006. DWAB4 Unified Web Evaluation Methodology (UWEM 1.0). Technical Report, WAB Cluster.

[25] Vigo, M., Brajnik, G., 2011. Automatic web accessibility metrics: where we are and where we can go. Interact. Comput., 23(2): 137-155. [