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Bundle Recommendation and Generation With Graph Neural Networks | IEEE Journals & Magazine | IEEE Xplore

Bundle Recommendation and Generation With Graph Neural Networks


Abstract:

Bundle recommendation aims to recommend a bundle of items for a user to consume as a whole. Related work can be divided into two categories: 1) to recommend the platform'...Show More

Abstract:

Bundle recommendation aims to recommend a bundle of items for a user to consume as a whole. Related work can be divided into two categories: 1) to recommend the platform's prebuilt bundles to users; 2) generate personalized bundles for users. In this work, we propose two graph neural network models, a BGCN model (short for Bundle Graph Convolutional Network) for prebuilt bundle recommendation, and a BGGN model (short for Bundle Graph Generation Network) for personalized bundle generation. First, BGCN unifies the user-item interaction, the user-bundle interaction and the bundle-item affiliation into a heterogeneous graph. With item nodes as the bridge, graph convolutional propagation between user and bundle nodes makes the learned representations capture the item-level semantics. Second, BGGN re-constructs bundles into graphs based on the item co-occurrence pattern and the user's supervision signal. The complex and high-order item-item relationships in the bundle graph are explicitly modeled through graph generation. Empirical results demonstrate the substantial performance gains of BGCN and BGGN, which outperforms the state-of-the-art baselines by 10.77% to 23.18% and 20.90% to 64.52%, respectively. We have released the datasets and codes at this link: https://github.com/cjx0525/BGCN.
Published in: IEEE Transactions on Knowledge and Data Engineering ( Volume: 35, Issue: 3, 01 March 2023)
Page(s): 2326 - 2340
Date of Publication: 22 September 2021

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1 Introduction

A BUNDLE is multiple items that are similar or complementary to meet users’ complex needs. Therefore, a good bundle can improve the user experience by satisfying multiple interests of users at the same time. Besides, it can also increase business sales by setting overall discounts to attract users to interact with larger orders. The prevalence of bundled items on e-commerce and content platforms makes bundle recommendation an important task.

References

References is not available for this document.