Towards Social Care Prediction Services Aided by Multi-agent Systems

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10685)


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 research work is supported 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

  1. 1.Ontology Engineering GroupUniversidad Politécnica de MadridMadridSpain

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