Development of an ontology for the inclusion of app users with visual impairments
Metadatos
Afficher la notice complèteEditorial
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Materia
Ontology Disability ICF Accessibility User profile Inclusion Apps Mobile devices
Date
2021Referencia bibliográfica
M. I. Torres-Carazo, M. J. Rodríguez-Fórtiz and M. V. H. Torres, "Development of an Ontology for the Inclusion of App Users With Visual Impairments," in IEEE Access, vol. 9, pp. 44339-44353, 2021, doi: 10.1109/ACCESS.2021.3065274.
Patrocinador
Spanish Ministry of Economy and Competitiveness (Agencia Estatal de Investigacion) PID2019-109644RB-I00/AEI/10.13039/501100011033Résumé
Approximately 15% of the world’s population have some form of disability and the majority
use apps on their mobile devices to help them in their daily lives with communication, healthcare, or for
entertainment purposes. It is not, however, easy for users with impairments to choose the most suitable apps
since this will depend on their particular personal characteristics or circumstances in a specific context, and
because such users require apps with certain accessibility features which are not always specified in the app
description. In order to overcome such difficulties, it is necessary to obtain a user profile that gathers the
user’s personal details, abilities, disabilities, skills, and interests to facilitate selection. The basis for our
research work is to develop an app that recommends a set of apps to users with disabilities. In this respect,
the focus of this paper is to obtain a semantic user profile model on which more precise search requests can
be performed. The disability we have chosen to concentrate on is that of visual impairment. We propose an
ontology-based user profile that matches users’ characteristics, disabilities, and interests, and which not
only simplifies the classification process but also provides a mechanism for linking them with existing
disability ontologies, assistive devices, accessibility concepts, etc. Moreover, thanks to the inclusion of
semantic relations and rules, it is possible to reason and infer new information that can be used to make
more personalized recommendations than a simple app store search.