4.6 Article

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

出版社

KOREA INFORMATION PROCESSING SOC
DOI: 10.22967/HCIS.2021.11.017

关键词

Accessibility; Adaptive Systems; Web Mining; Machine Learning

资金

  1. University of the Basque Country UPV/EHU [PIF15/143]
  2. Department of Education, Universities and Research of the Basque Government [IT980-16]
  3. Ministry of Economy and Competitiveness of the Spanish Government
  4. ERDF [TIN2017-85409-P]

向作者/读者索取更多资源

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. Automatic detection of user abilities and disabilities is the foundation for building adaptive systems, contributing to diminishing the digital divide for people with disabilities.
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.

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