Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Multi-agent Architecture for Labeling Data and Generating Prediction Models in the Field of Social Services
Year:2017
Research Areas
  • Artificial intelligence
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 di?culty 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
No
Congress
Practical Applications of Agents and Multi-Agent Systems
960
Place
Oporto
Reviewers
Si
ISBN/ISSN
978-3-319-60285-1
https://doi.org/10.1007/978-3-319-60285-1_15
Start Date
21/06/2017
End Date
23/06/2017
From page
177
To page
184
Multi-agent Architecture for Labeling Data and Generating Prediction Models in the Field of Social Services
Participants
  • Autor: Emilio Serrano Fernandez (UPM)
  • Autor: Pedro del Pozo Jimenez (UPM)
  • Autor: M. Carmen Suarez de Figueroa Baonza (UPM)
  • Autor: Jacinto Gonzalez Pachon (UPM)
  • Autor: Javier Bajo Perez (UPM)
  • Autor: Asuncion de Maria Gomez Perez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Economía y Sostenibilidad del Medio Natural
  • Departamento: Inteligencia Artificial
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