Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.26/18225
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dc.contributor.authorSapateiro, Cláudio-
dc.contributor.authorGomes, João-
dc.date.accessioned2017-04-21T11:32:41Z-
dc.date.available2017-04-21T11:32:41Z-
dc.date.issued2017-04-
dc.identifier.urihttp://hdl.handle.net/10400.26/18225-
dc.descriptionTrabalho apresentado no 5th World Conference on Information Systems and Technologies (WorldCIST’17), 11-13 de abril 2017, Porto Santo, Madeira Portugalpt_PT
dc.description.abstractAs a websites’ structure grow it is paramount to accommodate the alignment of user needs and experience with the overall websites’ purposes. Toward this requirement, the proposed website navigation recommendation system suggests to users, pages that might be of her interest based on past successful navigation patterns of overall site’s usage. Most of existing recommendation systems adopts traditionally one of the web mining branches. We take a different stance, on web mining usage, and alternatively considered the real time enactment of web analytic tools supported analysis given their current maturity and affordances. On this basis we provide a model, its implementation and evaluation for navigation based recommendations generation and delivery. The developed prototype adopted a SaaS orientation to promote the underlying functionalities integration within any website. Preliminary evaluation’s results seem to favor the validation of the present contribution rational.pt_PT
dc.language.isoengpt_PT
dc.rightsopenAccesspt_PT
dc.subjectWeb analyticspt_PT
dc.subjectRecommendation systemspt_PT
dc.subjectWeb usage recommendationpt_PT
dc.subjectNavigation recommendationspt_PT
dc.subjectUser Experiencept_PT
dc.titleLeverage web analytics for real time website browsing recommendationspt_PT
dc.typeconferenceObjectpt_PT
dc.description.versionN/Apt_PT
degois.publication.locationPorto Santo, Madeira, Portugalpt_PT
degois.publication.title5th World Conference on Information Systems and Technologies (WorldCIST’17)pt_PT
dc.peerreviewedyespt_PT
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