Web Mining for navigation problem detection and diagnosis in Discapnet: a website aimed at disabled people

The dramatic increase in the amount of information stored on the web makes it more important to familiarize people with disabilities and elderly people with digital devices and applications and to adapt websites to enable their use by these users. Discapnet is a website mainly aimed at visually disa...

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Detalles Bibliográficos
Autores: Arbelaiz Gallego, Olatz, Lojo Novo, Aizea;, Muguerza Rivero, Javier Francisco, Perona Balda, Iñigo
Tipo de recurso: artículo
Fecha de publicación:2015
País:España
Institución:Universidad del País Vasco
Repositorio:Addi. Archivo Digital para la Docencia y la Investigación
OAI Identifier:oai:addi.ehu.eus:10810/75020
Acceso en línea:http://hdl.handle.net/10810/75020
Access Level:acceso abierto
Palabra clave:Web accessibility
Web usability
Disabled users
Navigation problems
User experience
Web interaction
User modeling
Server logs
Web-usage mining
Clustering
Discapnet
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spelling Web Mining for navigation problem detection and diagnosis in Discapnet: a website aimed at disabled peopleArbelaiz Gallego, OlatzLojo Novo, Aizea;Muguerza Rivero, Javier FranciscoPerona Balda, IñigoWeb accessibilityWeb usabilityDisabled usersNavigation problemsUser experienceWeb interactionUser modelingServer logsWeb-usage miningClusteringDiscapnetThe dramatic increase in the amount of information stored on the web makes it more important to familiarize people with disabilities and elderly people with digital devices and applications and to adapt websites to enable their use by these users. Discapnet is a website mainly aimed at visually disabled people, and navigation is a challenging task for its users. In this context, system evaluation and problem detection become crucial aspects for enhancing user experience and may contribute greatly to diminishing the existing technological gap. This study proposes a system based on web-mining techniques that collects in-use information while the user is accessing the web (thus, being a noninvasive system). The proposed system models users in the wild and discovers navigation problems appearing in Discapnet and can also be used for problem detection when new users are navigating the site. The system was tested and its efficiency demonstrated in an experiment involving navigation under supervision, in which 82.6% of a set of disabled people were automatically labeled as having problems with the website.This work was funded by the Department of Education, Universities and Research of the Basque Government (Eusko Jaurlaritza/Gobierno Vasco) through Grant IT-395-10 and by the Science and Education Department of the Spanish Government (ModelAccess project, TIN2010-15549).Wiley202520252015info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10810/75020reponame:Addi. Archivo Digital para la Docencia y la Investigacióninstname:Universidad del País VascoIngléshttps://doi.org/10.1002/asi.23506info:eu-repo/semantics/openAccess© 2015 ASIS&T published by Wileyoai:addi.ehu.eus:10810/750202026-06-18T09:23:17Z
dc.title.none.fl_str_mv Web Mining for navigation problem detection and diagnosis in Discapnet: a website aimed at disabled people
title Web Mining for navigation problem detection and diagnosis in Discapnet: a website aimed at disabled people
spellingShingle Web Mining for navigation problem detection and diagnosis in Discapnet: a website aimed at disabled people
Arbelaiz Gallego, Olatz
Web accessibility
Web usability
Disabled users
Navigation problems
User experience
Web interaction
User modeling
Server logs
Web-usage mining
Clustering
Discapnet
title_short Web Mining for navigation problem detection and diagnosis in Discapnet: a website aimed at disabled people
title_full Web Mining for navigation problem detection and diagnosis in Discapnet: a website aimed at disabled people
title_fullStr Web Mining for navigation problem detection and diagnosis in Discapnet: a website aimed at disabled people
title_full_unstemmed Web Mining for navigation problem detection and diagnosis in Discapnet: a website aimed at disabled people
title_sort Web Mining for navigation problem detection and diagnosis in Discapnet: a website aimed at disabled people
dc.creator.none.fl_str_mv Arbelaiz Gallego, Olatz
Lojo Novo, Aizea;
Muguerza Rivero, Javier Francisco
Perona Balda, Iñigo
author Arbelaiz Gallego, Olatz
author_facet Arbelaiz Gallego, Olatz
Lojo Novo, Aizea;
Muguerza Rivero, Javier Francisco
Perona Balda, Iñigo
author_role author
author2 Lojo Novo, Aizea;
Muguerza Rivero, Javier Francisco
Perona Balda, Iñigo
author2_role author
author
author
dc.subject.none.fl_str_mv Web accessibility
Web usability
Disabled users
Navigation problems
User experience
Web interaction
User modeling
Server logs
Web-usage mining
Clustering
Discapnet
topic Web accessibility
Web usability
Disabled users
Navigation problems
User experience
Web interaction
User modeling
Server logs
Web-usage mining
Clustering
Discapnet
description The dramatic increase in the amount of information stored on the web makes it more important to familiarize people with disabilities and elderly people with digital devices and applications and to adapt websites to enable their use by these users. Discapnet is a website mainly aimed at visually disabled people, and navigation is a challenging task for its users. In this context, system evaluation and problem detection become crucial aspects for enhancing user experience and may contribute greatly to diminishing the existing technological gap. This study proposes a system based on web-mining techniques that collects in-use information while the user is accessing the web (thus, being a noninvasive system). The proposed system models users in the wild and discovers navigation problems appearing in Discapnet and can also be used for problem detection when new users are navigating the site. The system was tested and its efficiency demonstrated in an experiment involving navigation under supervision, in which 82.6% of a set of disabled people were automatically labeled as having problems with the website.
publishDate 2015
dc.date.none.fl_str_mv 2015
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10810/75020
url http://hdl.handle.net/10810/75020
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://doi.org/10.1002/asi.23506
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
© 2015 ASIS&T published by Wiley
eu_rights_str_mv openAccess
rights_invalid_str_mv © 2015 ASIS&T published by Wiley
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Wiley
publisher.none.fl_str_mv Wiley
dc.source.none.fl_str_mv reponame:Addi. Archivo Digital para la Docencia y la Investigación
instname:Universidad del País Vasco
instname_str Universidad del País Vasco
reponame_str Addi. Archivo Digital para la Docencia y la Investigación
collection Addi. Archivo Digital para la Docencia y la Investigación
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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