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Emotion-Based Recommender System for Overcoming the Problem of Information Overload

  • Hernani Costa
  • Luis Macedo
Part of the Communications in Computer and Information Science book series (CCIS, volume 365)

Abstract

Nowadays, we are experiencing a huge growth in the available information, caused by the advent of communication technology, which humans cannot handle by themselves. Personal Assistant Agents can help humans to cope with the task of selecting the relevant information. In order to perform well, these agents should consider not only their preferences, but also their mental states (such as beliefs, intentions and emotions) when recommending information. In this paper, we describe an ongoing Recommender System application, that implements a Multiagent System, with the purpose of gathering heterogeneous information from different sources and selectively deliver it based on: user’s preferences; the community’s trends; and on the emotions that it elicits in the user.

Keywords

information overload multiagent systems personal assistant agents recommender systems user modeling 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hernani Costa
    • 1
  • Luis Macedo
    • 1
  1. 1.CISUCUniversity of CoimbraPortugal

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