Personal and Ubiquitous Computing

, Volume 16, Issue 5, pp 597–610 | Cite as

Generating recommendations for consensus negotiation in group personalization services

  • Maria Salamó
  • Kevin McCarthy
  • Barry Smyth
Original Article


There are increasingly many personalization services in ubiquitous computing environments that involve a group of users rather than individuals. Ubiquitous commerce is one example of these environments. Ubiquitous commerce research is highly related to recommender systems that have the ability to provide even the most tentative shoppers with compelling and timely item suggestions. When the recommendations are made for a group of users, new challenges and issues arise to provide compelling item suggestions. One of the challenges a group recommender system must cope with is the potentially conflicting preferences of multiple users when selecting items for recommendation. In this paper, we focus on how individual user models can be aggregated to reach a consensus on recommendations. We describe and evaluate nine different consensus strategies and analyze them to highlight the benefits of group recommendation using live-user preference data. Moreover, we show that the performance is significantly different among strategies.


Consensus Group recommendation Ubiquitous personalization services 



This work has been supported in part by projects TIN2009-14404-C02, CONSOLIDER-INGENIO CSD 2007-00018 and also by Science Foundation Ireland under Grant No. 07/CE/11147 CLARITY CSET.


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.Dept. Matemàtica Aplicada i AnàlisiUniversitat de BarcelonaBarcelonaSpain
  2. 2.Clarity, School of Computer Science and Informatics, Science NorthUniversity College DublinDublin 4Ireland

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