Emotions ontology for collaborative modelling and learning of emotional responses.
Emotions-aware applications are getting a lot of attention as a way to improve the user experience, and also thanks to increasingly affordable Brain–Computer Interfaces (BCI). Thus, projects collecting emotion-related data are proliferating, like social networks sentiment analysis or tracking studen...
| Published in: | Computers in Human Behavior Vol. 51; pp. 610 - 618 |
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| Main Authors: | , , , |
| Format: | Article |
| Published: |
Elsevier B.V.
Oct2015 Part B
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=108614391&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 108614391 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 07475632 JC4 jtl: Computers in Human Behavior issn: 07475632 maglogo: N pubinfo: dt: Oct2015 Part B vid: 51 pid: 2410 pub: Elsevier B.V. artinfo: ui: 108614391 10.1016/j.chb.2014.11.100 ppf: 610 ppct: 8 formats: tig: atl: Emotions ontology for collaborative modelling and learning of emotional responses. aug: au: Gil, Rosa Virgili-Gomá, Jordi García, Roberto Mason, Cindy affil: Universitat de Lleida, Spain Computer Science Department, Stanford University, USA su: School dropouts Emotions Interprofessional relations Social networks Students Ontologies (Information retrieval) sug: subj: School dropouts Emotions Interprofessional relations Social networks Students Other Individual and Family Services Ontologies (Information retrieval) keyword: Affective computing Collaborative learning Emotion Knowledge representation Ontology Affective computing Collaborative learning Emotion Knowledge representation Ontology ab: Emotions-aware applications are getting a lot of attention as a way to improve the user experience, and also thanks to increasingly affordable Brain–Computer Interfaces (BCI). Thus, projects collecting emotion-related data are proliferating, like social networks sentiment analysis or tracking students’ engagement to reduce Massive Online Open Courses (MOOCs) drop out rates. All them require a common way to represent emotions so it can be more easily integrated, shared and reused by applications improving user experience. Due to the complexity of this data, our proposal is to use rich semantic models based on ontology. EmotionsOnto is a generic ontology for describing emotions and their detection and expression systems taking contextual and multimodal elements into account. The ontology has been applied in the context of EmoCS, a project that collaboratively collects emotion common sense and models it using the EmotionsOnto and other ontologies. Currently, emotion input is provided manually by users. However, experiments are being conduced to automatically measure users’s emotional states using Brain–Computer Interfaces. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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