Strategy-aware Bundle Recommender System
Yinwei Wei, Xiaohao Liu, Yunshan Ma, Xiang Wang, Liqiang Nie, Tat-Seng Chua
Abstract
A bundle is a group of items that provides improved services to users and increased profits for sellers. However, locating the desired bundles that match the users' tastes still challenges us, due to the sparsity issue. Despite the remarkable performance of existing approaches, we argue that they seldom consider the bundling strategy (i.e., how the items within a bundle are associated with each other) in the bundle recommendation, resulting in the suboptimal user and bundle representations for their interaction prediction. Therefore, we propose to model the strategy-aware user and bundle representations for the bundle recommendation.
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Cited by top-tier papers7
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- Adaptive In-Context Learning with Large Language Models for Bundle GenerationZhu Sun, Kaidong Feng, Jie Yang, Xinghua Qu et al.SIGIR 2024 · 9 citations
- Disentangled Contrastive Bundle Recommendation with Conditional DiffusionJiuqiang LiAAAI 2025 · 5 citations
- Fine-tuning Multimodal Large Language Models for Product BundlingXiaohao Liu, Jie Wu, Zhulin Tao, Yunshan Ma et al.KDD 2025 · 3 citations
- Modeling Item-Level Dynamic Variability with Residual Diffusion for Bundle RecommendationDong Zhang, Lin Li, Ming Li, Amran Bhuiyan et al.AAAI 2026 · 2 citations
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