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Algorithms for Group Recommendation

  • Alexander Felfernig
  • Ludovico Boratto
  • Martin Stettinger
  • Marko Tkalčič
Chapter
Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Abstract

In this chapter, our aim is to show how group recommendation can be implemented on the basis of recommendation paradigms for individual users. Specifically, we focus on collaborative filtering, content-based filtering, constraint-based, critiquing-based, and hybrid recommendation. Throughout this chapter, we differentiate between (1) aggregated predictions and (2) aggregated models as basic strategies for aggregating the preferences of individual group members.

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Copyright information

© The Author(s) 2018

Authors and Affiliations

  • Alexander Felfernig
    • 1
  • Ludovico Boratto
    • 2
  • Martin Stettinger
    • 1
  • Marko Tkalčič
    • 3
  1. 1.Institute for Software TechnologyGraz University of TechnologyGrazAustria
  2. 2.EURECATCentre Tecnológico de CatalunyaBarcelonaSpain
  3. 3.Faculty of Computer ScienceFree University of Bozen-BolzanoBolzanoItaly

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