OPTIMAL-EM: An AI-Driven Framework for Systematic Web Accessibility Evaluation
Primary supervisor
Additional supervisors
- Yeliz Yesilada
Additional information
- OPTIMAL-EM: A Software Tool for Optimised Web Accessibility Evaluation -- Software
- OPTIMAL-EM: Accessibility and Complexity Analysis Pipeline
- Optimising web accessibility evaluation: Population sourcing methods for web accessibility evaluation
- OPTIMAL-EM: Optimised Population Sourcing for Web Accessibility Evaluation
- Web Structure Derived Clustering for Optimised Web Accessibility Evaluation
Contact admissions office
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Funding
- Competition Funded Project (Students Worldwide)
This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. Applications for this project are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full department and project details for further information.
Project description
Web accessibility means people with varying capabilities can easily access web pages and applications. Website Accessibility Conformance Evaluation Methodology (WCAG-EM) is a de-facto methodology for evaluating accessibility. OPTIMAL-EM aims to address the limitations of this methodology by optimizing the sampling of web pages to provide a scientific approach to the evaluation process. OPTIMAL-EM comprises six key metrics: coverage, complexity, accessibility, representativeness, popularity, and freshness. It allows the sampling of web pages using artificial intelligence techniques, mainly unsupervised learning, to decide how to choose pages. This PhD project aims to focus on researching and developing OPTIMAL-EM further, in particular by addressing the following: (1) investigating the effects of the metrics such as popularity freshness; (2) researching heuristics and parameter tuning techniques for unsupervised learning algorithms for parameter selection on different websites; (3) developing an integrated application to support OPTIMAL-EM; (4) empirically validating OPTIMAL-EM.
Person specification
For information
- Candidates must hold a minimum of an upper Second Class UK Honours degree or international equivalent in a relevant science or engineering discipline.
- Candidates must meet the School's minimum English Language requirement.
- Candidates will be expected to comply with the University's policies and practices of equality, diversity and inclusion.
Essential
Applicants will be required to evidence the following skills and qualifications.
- You must be capable of performing at a very high level.
- You must have a self-driven interest in uncovering and solving unknown problems and be able to work hard and creatively without constant supervision.
Desirable
Applicants will be required to evidence the following skills and qualifications.
- You will have good time management.
- You will possess determination (which is often more important than qualifications) although you'll need a good amount of both.
General
Applicants will be required to address the following.
- Comment on your transcript/predicted degree marks, outlining both strong and weak points.
- Discuss your final year Undergraduate project work - and if appropriate your MSc project work.
- How well does your previous study prepare you for undertaking Postgraduate Research?
- Why do you believe you are suitable for doing Postgraduate Research?