An Interpretable Neural Network Model for Bundle Recommendations

Xinyi Li, Edward Carl Malthouse · 2022

A users’ preference for a bundle – a set of items that can be purchased together – can be expressed by the utility of this bundle to the user. The multi-attribute utility theory motivate us to characterize the utility of a bundle using its attributes to improve the personalized bundle recommendation systems. This extended abstract for the Doctoral Symposium describes my PhD project for studying the utility of a bundle using its attributes. The steps taken and some preliminary results are presented, with an outline of the future plans.

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