Making Recommendations for Groups Using Collaborative Filtering and Fuzzy Majority

  • Sérgio R. de M. Queiroz
  • Francisco de A. T. de Carvalho
  • Geber L. Ramalho
  • Vincent Corruble
Conference paper

DOI: 10.1007/3-540-36127-8_24

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2507)
Cite this paper as:
Queiroz S.R..M., de Carvalho F..A.T., Ramalho G.L., Corruble V. (2002) Making Recommendations for Groups Using Collaborative Filtering and Fuzzy Majority. In: Bittencourt G., Ramalho G.L. (eds) Advances in Artificial Intelligence. SBIA 2002. Lecture Notes in Computer Science, vol 2507. Springer, Berlin, Heidelberg

Abstract

In recent years, recommender systems have achieved a great success. Popular sites like Amazon.com and CDNow give thousands of recommendations every day. However, although many activities are carried out in groups, like going to the theater with friends, these systems are focused on recommending items for individual users. This brings out the need of systems capable of performing recommendations for groups of people, a domain that has received little attention in the literature. In this article we introduce an investigation of automatic group recommendations, making connections with problems considered in social choice and psychology. Then we suggest a novel method of making recommendations for groups, based on existing techniques of collaborative filtering and classification of alternatives using fuzzy majority. Finally we experimentally evaluate the proposed method to see its behavior under groups of different sizes and degrees of homogeneity.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Sérgio R. de M. Queiroz
    • 1
  • Francisco de A. T. de Carvalho
    • 1
  • Geber L. Ramalho
    • 1
  • Vincent Corruble
    • 2
  1. 1.Centra de Informática — Cin/UFPE - CxRecifeBrazil
  2. 2.Laboratoire d’Informatique de Paris VI - LIP6 — 4ParisFrance

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