Conference of the Spanish Association for Artificial Intelligence

Advances in Artificial Intelligence pp 187-197 | Cite as

Learning Parliamentary Profiles for Recommendation Tasks

  • Luis M. de Campos
  • Juan M. Fernández-Luna
  • Juan F. Huete
  • Pável Calado
  • Bruno Martins
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9422)

Abstract

We consider the problem of building a content-based recommender system in a parliamentary context, which may be used for two different but related tasks. First, we consider a filtering task where, given a new document to be recommended, the system can decide those Members of the Parliament who should receive it. Second, we also consider a recommendation task where, given a request from a citizen, the system should present information on those deputies that are more involved in the topics of the request. To build the system we collected, for each Member of the Parliament, the text of corresponding speeches within the parliament debates and generated, with different techniques, a profile that was used to match against the input (document or request). We tested our methods using the documents of the regional Andalusian Parliament at Spain, obtaining promising results.

Keywords

User profiles Content-based recommender systems Information filtering Information retrieval Parliamentary documents 

Notes

Acknowledgements

Paper supported by the Spanish “Ministerio de Economía y Competitividad” under the project TIN2013-42741-P.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Luis M. de Campos
    • 1
  • Juan M. Fernández-Luna
    • 1
  • Juan F. Huete
    • 1
  • Pável Calado
    • 2
  • Bruno Martins
    • 2
  1. 1.Departamento de Ciencias de la Computación e Inteligencia Artificial, ETSI Informática y de Telecomunicación, CITIC-UGRUniversidad de GranadaGranadaSpain
  2. 2.Instituto Superior Técnico e INESC-IDUniversidade de LisboaLisboaPortugal

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