This paper proposes a Decision-Guided Group Package Recommender (DG-GPR) framework, which provides recommendations on dynamically defined packages of products and services. This framework is based on: (1) defining the space of alternatives; (2) eliciting the utility function for each individual decision maker; (3) estimating the group utility function; (4) using the group utility function to find an optimal recommendation alternative; (5) constructing a set of diverse recommendations which contains the optimal recommendation alternative; and (6) applying a Hybrid Condorcet-Instant Runoff Voting method from social choice theories, to refine the recommendations. A preliminary experimental study is conducted which shows that the proposed framework significantly outperforms its previous extension which in turn had previously outperformed three popular aggregation strategies.
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