Aggregation of Preferences in Recommender Systems

  • Gleb Beliakov
  • Tomasa Calvo
  • Simon James


This chapter gives an overview of aggregation functions toward their use in recommender systems. Simple aggregation functions such as the arithmetic mean are often employed to aggregate user features, item ratings, measures of similarity, etc., however many other aggregation functions exist which could deliver increased accuracy and flexibility to many systems. We provide definitions of some important families and properties, sophisticated methods of construction, and various examples of aggregation functions in the domain of recommender systems.


Recommender System Aggregation Function Aggregation Operator Fuzzy Measure Similar User 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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T. Calvo wishes to acknowledge her support from the projects MTM2006-08322 and PR2007-0193 from Ministerio de Educación y Ciencia, Spain and the EU project 143423-2008-LLP-ES-KA3-KA3MP.


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.School of Information TechnologyDeakin UniversityBurwoodAustralia
  2. 2.Departamento de Ciencias de la ComputaciónUniversidad de AlcaláAlcalá de Henares (Madrid)Spain

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