Archive

Lecture: Prof. Francesco Ricci, Group Recommender Systems: Rank Aggregation and Balancing Techniques

beginning: 26.04.2013
hour: 10:00
location: Multimedia room

 

Prof. Francesco Ricci
Faculty of Computer Science
Free University of Bozen-Bolzano, Italy

Group Recommender Systems: Rank Aggregation and Balancing Techniques

The majority of recommender systems are designed to make recommendations for individual users. However, in some circumstances the items to be selected are not intended for personal usage but for a group; e.g., a DVD could be watched by a group of friends. In order to generate effective recommendations for a group the system must satisfy, as much as possible, the individual preferences of the group’s members.

In this talk we introduce some important technical issues related to the design of groups recommender systems. We then illustrate the effectiveness of group recommendations obtained aggregating the individual lists of recommendations produced by a collaborative filtering system. We have compared off line the ranking quality of individual and group recommendation lists. We observe that the effectiveness of a group recommendation does not necessarily decrease when the group size grows and that group recommendations are not necessarily worse than individual recommendations. Finally, we illustrate the results of an online experiment where a sequential group recommender system was tested and users compared system generated vs. user generated group recommendations.