dc.creatorGomes Cardoso,Ismael
dc.creatorMota,Bruno
dc.creatorVictória Barbosa,Jorge Luis
dc.creatorda Rosa Righi,Rodrigo
dc.date2016-04-01
dc.date.accessioned2023-09-25T18:35:54Z
dc.date.available2023-09-25T18:35:54Z
dc.identifierhttp://www.scielo.edu.uy/scielo.php?script=sci_arttext&pid=S0717-50002016000100006
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/8838782
dc.descriptionEven though the use of recommender systems is already widely spread in several application areas, there is still a lack of studies for accessibility research field. One of these attempts to use recommender system benefits for accessibility needs is Vulcanus. The Vulcanus recommender system uses similarity analysis to compare user’s trails. In this way, it is possible to take advantage of the user’s past behavior and distribute personalized content and services. The Vulcanus combined concepts from ubiquitous computing, such as user profiles, context awareness, trails management, and similarity analysis. It uses two different approaches for trails similarity analysis: resources patterns and categories patterns. In this work we performed an asymptotic analysis, identifying Vulcanus’ algorithm complexity. Furthermore we also propose improvements achieved by dynamic programming technique, so the ordinary case is improved by using a bottom-up approach. With that approach, many unnecessary comparisons can be skipped and now Vulcanus 2.0 is presented with improvements in its average case scenario.
dc.formattext/html
dc.languageen
dc.publisherCentro Latinoamericano de Estudios en Informática
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceCLEI Electronic Journal v.19 n.1 2016
dc.subjectRecommender System
dc.subjectAccessibility
dc.subjectContext Awareness
dc.subjectAsymptotic Analysis
dc.titleVulcanus 2.0: A Recommender System for Accessibility
dc.typeinfo:eu-repo/semantics/article


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