Towards social care prediction services aided by multi-agent systems

Serrano Fernández, Emilio and Bajo Pérez, Javier (2017). Towards social care prediction services aided by multi-agent systems. In: "10th International Workshop, A2HC 2017 and International Workshop, A-HEALTH 2017", 21 Jun 2017, Oporto, Portugal. ISBN 978-3-319-70886-7. pp. 119-130. https://doi.org/10.1007/978-3-319-70887-4_7.

Description

Title: Towards social care prediction services aided by multi-agent systems
Author/s:
  • Serrano Fernández, Emilio
  • Bajo Pérez, Javier
Item Type: Presentation at Congress or Conference (Article)
Event Title: 10th International Workshop, A2HC 2017 and International Workshop, A-HEALTH 2017
Event Dates: 21 Jun 2017
Event Location: Oporto, Portugal
Title of Book: Agents and Multi-Agent Systems for Health Care: A2HC 2017, AHEALTH 2017
Date: 2017
ISBN: 978-3-319-70886-7
Subjects:
Freetext Keywords: Multi-agent systems; Human-agent societies; Social services; Machine learning
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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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.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTIN2016-78011-C4-4-RUnspecifiedUniversidad Politécnica de MadridDatos 4.0: retos y soluciones

More information

Item ID: 50223
DC Identifier: http://oa.upm.es/50223/
OAI Identifier: oai:oa.upm.es:50223
DOI: 10.1007/978-3-319-70887-4_7
Official URL: https://link.springer.com/chapter/10.1007/978-3-319-70887-4_7
Deposited by: Memoria Investigacion
Deposited on: 05 Jun 2019 11:26
Last Modified: 05 Jun 2019 11:26
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