Automatic Web Navigation Problem Detection Based on Client-Side Interaction Data

Yera A., Perona I., Arbelaitz O., Muguerza J., Pérez J. E., Valencia X.

2021 - Human-centric Computing and Information Sciences Vol. 11

Journal paper

Línea investigación:
Web Accessibility
Authors by signature order:
Yera A., Perona I., Arbelaitz O., Muguerza J., Pérez J. E., Valencia X.
Description:

The current importance of digital competence makes it essential to enable people with disabilities to use digital devices and applications and to automatically adapt site interactions to their needs. Although most of the current adaptable solutions make use of predefined user profiles, automatic detection of user abilities and disabilities is the foundation for building adaptive systems.This work contributes to diminishing the digital divide for people with disabilities by detecting the web navigation problems of users with physical disabilities based on a two-step strategy. The system is based on web user interaction data collected by the RemoTest platform and a complete data mining process applied to the data. First, the device used for interaction is recognized, and then, the problems the user may be having while interacting with the computer are detected. Identification of the device being used and the problems being encountered will allow the most adequate adaptation to be deployed and thus make the navigation more accessible.

Editorial:
KIPS-CSWRG
Publication year:
2021
Start page:
1
Final page:
16
File URL:
https://doi.org/10.22967/HCIS.2021.11.017
Quality indicators:
La revista HCIS ha tenido en 2019 un factor de impacto de 3,700 en ISI/JCR Science Edition, ocupando el puesto 37 de 156 revistas (Q1) en la categoría Computer Science, Information Systems. Asimismo, figura en la posición 45 de 280 revistas (Q1) en la categoría Computer Science (miscellaneous) de la clasificación SJR de Elsevier de 2019, con un factor de impacto de 0,661.
Publication name:
Human-centric Computing and Information Sciences Vol. 11
Volume:
11