Statistical machine learning methods applied in the study of web accessibility: a literature review
Vol. 1 No. Special (2022), Papers
Vol. 1 No. Special (2022)

Statistical machine learning methods applied in the study of web accessibility: a literature review

Papers
https://doi.org/10.47460/minerva.v1iSpecial.90
Published December 19, 2022
Zambrano Felix
Universidad Tecnica de Manabi. Portoviejo, Ecuador.
Munoz Emanuel
Universidad Tecnica de Manabi. Portoviejo, Ecuador.
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Keywords

accesibilidad web
machine learning
aprendizaje no supervisado
estadística

How to Cite

Zambrano, F., & Munoz, E. (2022). Statistical machine learning methods applied in the study of web accessibility: a literature review. Minerva, 1(Special), 150-157. https://doi.org/10.47460/minerva.v1iSpecial.90
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Abstract

An accessible website refers to the fact that any person, especially those with physical disabilities, can access the content of the website without problems. The objective of this research is the analysis through literature reviews of machine learning methods applied to the study of accessibility in the web portals of Decentralized Autonomous Governments. In addition, a systematic literature review methodology was used to review more than twenty scientific articles related to keywords such as web accessibility, statistics, and machine learning, among others. In the results obtained, several techniques stand out, especially those of unsupervised learning, since their usefulness was observed in several investigations, improving the analysis and understanding of the data. This research has shown that exciting work can be done on web accessibility in institutions, considering that these studies would significantly contribute to improving access to content.

https://doi.org/10.47460/minerva.v1iSpecial.90
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References

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