A Multi-agent Architecture for Labeling Data and Generating Prediction Models in the Field of Social Services

  • Emilio Serrano
  • Pedro del Pozo-Jiménez
  • Mari Carmen Suárez-Figueroa
  • Jacinto González-Pachón
  • Javier BajoEmail author
  • Asunción Gómez-Pérez
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 722)


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.


Multi-agent systems Human-agent societies Social services Machine learning 



This publication would not have been possible without the inputs and collaboration of the Social Services of Castilla y León. This research work is supported by the “Junta de Castilla y León” under the public contract: “Servicios de elaboración de modelos matemáticos para realizar segmentación poblacional” (A2016/000271); by the EU Programme for Employment and Social Innovation (EaSI) under the project PACT (“people-oriented case management for social inclusion proactive model”); and, by the Spanish Ministry of Economy, Industry and Competitiveness under the R&D project Datos 4.0: Retos y soluciones (TIN2016-78011-C4-4-R, AEI/FEDER, UE).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Emilio Serrano
    • 1
  • Pedro del Pozo-Jiménez
    • 1
  • Mari Carmen Suárez-Figueroa
    • 1
  • Jacinto González-Pachón
    • 1
  • Javier Bajo
    • 1
    Email author
  • Asunción Gómez-Pérez
    • 1
  1. 1.Ontology Engineering GroupUniversidad Politécnica de MadridMadridSpain

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