Designing a Belief Function-Based Accessibility Indicator to Improve Web Browsing for Disabled People

TL;DR

This paper introduces a belief function-based accessibility indicator for web pages, aiming to improve navigation for disabled users by fusing uncertain assessment data from automated tools.

Contribution

It presents a novel framework using belief functions to fuse uncertain accessibility reports, enhancing the accuracy of web accessibility evaluation.

Findings

The indicator effectively identifies accessibility issues across four deficiency categories.

Validation on 100 popular French news sites shows promising results.

The approach handles uncertainty and divergence in automated assessments.

Abstract

The purpose of this study is to provide an accessibility measure of web-pages, in order to draw disabled users to the pages that have been designed to be ac-cessible to them. Our approach is based on the theory of belief functions, using data which are supplied by reports produced by automatic web content assessors that test the validity of criteria defined by the WCAG 2.0 guidelines proposed by the World Wide Web Consortium (W3C) organization. These tools detect errors with gradual degrees of certainty and their results do not always converge. For these reasons, to fuse information coming from the reports, we choose to use an information fusion framework which can take into account the uncertainty and imprecision of infor-mation as well as divergences between sources. Our accessibility indicator covers four categories of deficiencies. To validate the theoretical approach in this context, we propose an evaluation completed on a corpus of 100 most visited French news websites, and 2 evaluation tools. The results obtained illustrate the interest of our accessibility indicator.