Boratto, Ludovico and Carta, Salvatore and Chessa, Alessandro and Agelli, Maurizio and Clemente, M. Laura Group Recommendation with Automatic Identification of Users Communities. In: Proceedings of the IEEE/WIC/ACM International Joint Conferences on eb Intelligence and Intelligent Agent Technologies, 2009. WI-IAT '09. IEEE, pp. 547-550. ISBN 978-1-4244-5331-3 (2009)Full text not available from this repository.
Recommender systems usually propose items to single users. However, in some domains like Mobile IPTV or Satellite Systems it might be impossible to generate a program schedule for each user, because of bandwidth limitations. A few approaches were proposed to generate group recommendations. However, these approaches take into account that groups of users already exist and no recommender system is able to detect intrinsic users communities. This paper describes an algorithm that detects groups of users whose preferences are similar and predicts recommendations for such groups. Groups of different granularities are generated through a modularity-based Community Detection algorithm, making it possible for a content provider to explore the trade off between the level of personalization of the recommendations and the number of channels. Experimental results show that the quality of group recommendations increases linearly with the number of groups created.
|Item Type:||Book Section|
|Uncontrolled Keywords:||collaborative filtering; community detection; recommender systems|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QC Physics
|Research Area:||Economics and Institutional Change|
|Depositing User:||Ms T. Iannizzi|
|Date Deposited:||07 Nov 2013 13:17|
|Last Modified:||07 Nov 2013 13:17|
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