Preference elicitation techniques for group recommender systems

@article{Garcia2012PreferenceET,
  title={Preference elicitation techniques for group recommender systems},
  author={Inma Garcia and Sergio Pajares and Laura Sebastia and Eva Onaindia},
  journal={Inf. Sci.},
  year={2012},
  volume={189},
  pages={155-175}
}
A key issue in group recommendation is how to combine the individual preferences of different users that form a group and elicit a profile that accurately reflects the tastes of all members in the group. Most Group Recommender Systems (GRSs) make use of some sort of method for aggregating the preference models of individual users to elicit a recommendation that is satisfactory for the whole group. In general, most GRSs offer good results, but each of them have only been tested in one… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 65 REFERENCES

Recommender systems handbook

J. Masthoff
  • Recommender Systems Handbook, Springer
  • 2011
VIEW 23 EXCERPTS
HIGHLY INFLUENTIAL

Group Modeling: Selecting a Sequence of Television Items to Suit a Group of Viewers

  • Personalized Digital Television
  • 2004
VIEW 9 EXCERPTS
HIGHLY INFLUENTIAL

The adaptive web

R. Burke
  • The Adaptive Web, Springer Berlin / Heidelberg
  • 2007
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL