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dc.contributor.authorSusaiyah, Allmin
dc.contributor.authorHärmä, Aki
dc.contributor.authorReiter, Ehud
dc.contributor.authorPetković, Milan
dc.date2021-03
dc.date.accessioned2022-04-21T08:51:32Z
dc.date.available2022-04-21T08:51:32Z
dc.identifier.issn1989-1660
dc.identifier.urihttps://reunir.unir.net/handle/123456789/12886
dc.description.abstractInsights derived from wearable sensors in smartwatches or sleep trackers can help users in approaching their healthy lifestyle goals. These insights should indicate significant inferences from user behaviour and their generation should adapt automatically to the preferences and goals of the user. In this paper, we propose a neural network model that generates personalised lifestyle insights based on a model of their significance, and feedback from the user. Simulated analysis of our model shows its ability to assign high scores to a) insights with statistically significant behaviour patterns and b) topics related to simple or complex user preferences at any given time. We believe that the proposed neural networks model could be adapted for any application that needs user feedback to score logical inferences from data.es_ES
dc.language.isoenges_ES
dc.publisherInternational Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)es_ES
dc.relation.ispartofseries;vol. 6, nº 5
dc.relation.urihttps://www.ijimai.org/journal/bibcite/reference/2889es_ES
dc.rightsopenAccesses_ES
dc.subjectartificial intelligencees_ES
dc.subjectfeedbackes_ES
dc.subjectneural networkes_ES
dc.subjectself-supervised learninges_ES
dc.subjecttransfer learninges_ES
dc.subjectlogical inferencees_ES
dc.subjectnatural language generationes_ES
dc.subjectstatistical learninges_ES
dc.subjectIJIMAIes_ES
dc.titleNeural Scoring of Logical Inferences from Data using Feedbackes_ES
dc.typearticlees_ES
reunir.tag~IJIMAIes_ES
dc.identifier.doihttps://doi.org/10.9781/ijimai.2021.02.004


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