User profiles, such as age and interest tags, form the backbone of modern recommender systems. However, in real-world scenarios, user profiles frequently encounter the problem of incomplete profile data, restricting the effectiveness of downstream recommendation tasks. Although large language models (LLMs) have shown r...
Riwei Lai, Yun-Sheng Xia, Li Chen et al.· 0 citations
DivCDSR is proposed, a novel model-agnostic framework designed to enhance diversity in CDSR that introduces a dual-prototype semantic constraint mechanism that mitigates the homogenization trap via intra-domain clustering with orthogonalization and inter-domain separation and devise a dual-guided diffusion module that...
Shu Chen, Yu-Han Zhao, Weixin Chen et al.· Proceedings of the 32nd ACM...· 0 citations
While Cross-Domain Sequential Recommendation (CDSR) has proven effective in mitigating data sparsity and enhancing accuracy, its impact on recommendation diversity remains largely unexplored. We are the first to reveal a counterintuitive phenomenon: while CDSR improves accuracy, it often comes at the cost of diversity,...
Shu Chen, Yuhan Zhao, Weixin Chen et al.· Proceedings of the 32nd ACM...· 0 citations
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