State-of-the-Art in Group Recommendation and New Approaches for Automatic Identification of Groups

  • Ludovico Boratto
  • Salvatore Carta
Part of the Studies in Computational Intelligence book series (SCI, volume 324)

Abstract

Recommender systems are important tools that provide information items to users, by adapting to their characteristics and preferences. Usually items are recommended to individuals, but there are contexts in which people operate in groups. To support the recommendation process in social activities, group recommender systems were developed. Since different types of groups exist, group recommendation should adapt to them, managing heterogeneity of groups. This chapter will present a survey of the state-of-the-art in group recommendation, focusing on the type of group each system aims to. A new approach for group recommendation is also presented, able to adapt to technological constraints (e.g., bandwidth limitations), by automatically identifying groups of users with similar interests.

Keywords

Root Mean Square Error Recommender System Community Detection Collaborative Filter Technological Constraint 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Ludovico Boratto
    • 1
  • Salvatore Carta
    • 1
  1. 1.Dipartimento di Matematica e InformaticaUniversità di CagliariCagliariItaly

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