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Towards multimodal affective detection in educational systems through mining emotional data sources

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dc.contributor.authorSalmeron Majadas, Sergio
dc.contributor.authorSantos, Olga C.
dc.contributor.authorGonzález Boticario, Jesús
dc.coverage.spatialMadrid
dc.coverage.temporal2015-06-22
dc.date.accessioned2025-09-15T11:44:26Z
dc.date.available2025-09-15T11:44:26Z
dc.date.issued2015
dc.descriptionThe registered version of this conference paper, first published in "Conati, C., Heffernan, N., Mitrovic, A., Verdejo, M. (eds) Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science, vol 9112. Springer, Cham", is available online at the publisher's website: https://doi.org/10.1007/978-3-319-19773-9_133
dc.description.abstractThis paper introduces the work being carried out in an ongoing PhD research focused on the detection of the learners’ affective states by combining different available sources (from physiological sensors to keystroke analysis). Different data mining algorithms and data labeling techniques have been used generating 735 prediction models. Results so far show that predictive models on affective state detection from multimodal-based approaches provide better accuracy rates than single-based.en
dc.description.versionversión publicada
dc.identifier.citationSalmeron-Majadas, S., Santos, O.C., Boticario, J.G. (2015). Towards Multimodal Affective Detection in Educational Systems Through Mining Emotional Data Sources. In: Conati, C., Heffernan, N., Mitrovic, A., Verdejo, M. (eds) Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science(), vol 9112. Springer, Cham. https://doi.org/10.1007/978-3-319-19773-9_133
dc.identifier.doihttps://doi.org/10.1007/978-3-319-19773-9_133
dc.identifier.isbn9783319197722
dc.identifier.urihttps://hdl.handle.net/20.500.14468/30068
dc.language.isoen
dc.publisherSpringer Nature
dc.relation.centerE.T.S. de Ingeniería Informática
dc.relation.congressArtificial Intelligence in Education 17th International Conference, AIED 2015, Madrid, Spain, June 22-26, 2015
dc.relation.departmentInteligencia Artificial
dc.relation.projectidinfo:eu-repo/grantAgreement/MICINN/Programa Nacional de Investigación Fundamental/TIN2011-29221-C03-01/ES/ENFOQUES MULTIMODALES PARA EL MODELADO DE ASPECTOS EMOCIONALES EN ESCENARIOS DE EDUCACION PERSONALIZADOS E INCLUSIVOS EN CONTEXTOS INTELIGENTES
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject3304 Tecnología de los ordenadores
dc.subject.keywordsArtificial intelligenceen
dc.subject.keywordsAffective computingen
dc.subject.keywordsdata miningen
dc.subject.keywordsHuman- computer interactionen
dc.subject.keywordsAdaptive systemsen
dc.subject.keywordsUser modelingen
dc.subject.keywordsMachine learningen
dc.subject.keywordsMultimodal approachen
dc.subject.keywordsSensor dataen
dc.titleTowards multimodal affective detection in educational systems through mining emotional data sourcesen
dc.typeactas de congresoes
dc.typeconference proceedingsen
dspace.entity.typePublication
relation.isAuthorOfPublicationdf3339e5-d482-4ea3-85ad-3a554c2ba075
relation.isAuthorOfPublicatione067a1f1-6036-4974-a582-85b556587d18
relation.isAuthorOfPublication.latestForDiscoverydf3339e5-d482-4ea3-85ad-3a554c2ba075
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