Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Towards Social Care Prediction Services Aided by Multi-agent Systems
Year:2017
Research Areas
  • Information technology and adata processing
Information
Abstract
Prediction models are widely used in insurance companies and health services. Even when 120 million people are at risk of suffering poverty or social exclusion in the EU, this kind of models are surprisingly unusual in the field of social services. A fundamental reason for this gap is the difficulty in labeling and annotating social services data. Conditions such as social exclusion require a case-by-case debate. This paper presents a multi-agent architecture that combines semantic web technologies, exploratory data analysis techniques, and supervised machine learning methods. The architecture offers a holistic view of the main challenges involved in labeling data and generating prediction models for social services. Moreover, the proposal discusses to what extent these tasks may be automated by intelligent agents.
International
Si
Congress
Workshop on Agents and multi-agent Systems for AAL and e-HEALTH (A-HEALTH) at PAAMS 2017
960
Place
Oporto, Portugal
Reviewers
Si
ISBN/ISSN
978-3-319-70886-7
Start Date
21/06/2017
End Date
21/06/2017
From page
119
To page
130
PAAMS 2017 : 15th International Conference on Practical Applications of Agents and Multi-Agent Systems
Participants
  • Autor: Emilio Serrano Fernandez (UPM)
  • Autor: Javier Bajo Perez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial
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