Multi-Product Utility Maximization for Economic Recommendation

Basic economic relations such as substitutability and complementarity between products are crucial for recommendation tasks, since the utility of one product may depend on whether or not other products are purchased. For example, the utility of a camera lens could be high if the user possesses the right camera (complementarity), while the utility of another camera could be low because the user has already purchased one (substitutability). We propose \emph{multi-product utility maximization} (MPUM) as a general approach to recommendation driven by economic principles. MPUM integrates the economic theory of consumer choice with personalized recommendation, and focuses on the utility of \textit{sets} of products for individual users. MPUM considers what the users already have when recommending additional products. We evaluate MPUM against several popular recommendation algorithms on two real-world E-commerce datasets. Results confirm the underlying economic intuition, and show that MPUM significantly outperforms the comparison algorithms under top-K evaluation metrics.