A Survey on Bundle Recommendation: Methods, Applications, and Challenges

Understand

In recent years, bundle recommendation systems have gained significant attention in both academia and industry due to their ability to enhance user experience and increase sales by recommending a set of items as a bundle rather than individual items.

• This survey provides a comprehensive review on bundle recommendation, beginning by a taxonomy for exploring product bundling.
• We classify it into two categories based on bundling strategy from various application domains, i.e., discriminative and generative bundle recommendation.
• Then we formulate the corresponding tasks of the two categories and systematically review their methods: 1) representation learning from bundle and item levels and interaction modeling for discriminative bundle recommendation; 2) representation learning from item level and bundle generation for generative bundle recommendation.