Designing an ontology for emotion-driven visual representations

Rebecca Lin, Muhammad Amith, Chen Liang, Cui Tao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Emotions influence our perceptions and decisions and are often felt more strongly in situations related to healthcare. Therefore, it is important to understand how both providers and patients express their emotions in face-to-face scenarios. An ontology is a way to represent domain concepts and the relationships between them in a polyarchical manner. We have created an ontological model called the Visualized Emotion Ontology (VEO) that expresses the semantic definitions and visualizations of 25 emotions based on published research. With VEO, we can augment patient-facing software tools, like embodied conversational agents, to improve patient-provider interaction in clinical environments.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
EditorsIllhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1280-1283
Number of pages4
ISBN (Electronic)9781509030491
DOIs
StatePublished - Dec 15 2017
Externally publishedYes
Event2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States
Duration: Nov 13 2017Nov 16 2017

Publication series

NameProceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume2017-January

Conference

Conference2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Country/TerritoryUnited States
CityKansas City
Period11/13/1711/16/17

Keywords

  • crowdsourcing
  • graphical user interfaces
  • knowledge engineering
  • knowledge representation
  • public healthcare
  • semantic web
  • software agents

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

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