\Abstract

Group-based configuration is a fairly new configuration approach that presents a scenario where a group of people is configuring a product, service, or solution. However, good group decisions are difficult to arrive at. Therefore, to facilitate group decisions, group recommender systems are used. Yet, they have not been applied to group-based configuration. This thesis proposes a concept for an item based recommender system that helps a group to find a consensus for a configuration decision. The concept shows how preferences of individual group members can be combined to give configurations a group score. The score is used to rank configurations in a database and recommend the configuration with the highest score.
A prototype is implemented and evaluated with a newly introduced offline satisfaction metric and with synthetically generated groups. Overall the evaluation shows that the proposed concept works especially well for heterogeneous groups.
