生成式 AI 时代群体推荐系统再思考：从一次性推荐走向对话式群体决策支持
Rethinking Group Recommender Systems in the Era of Generative AI: From One-Shot Recommendations to Conversational Group Decision Support
AI 导读
arXiv 一篇论文指出，群体推荐系统虽有二十五年研究积累，但实际落地应用仍很少，现有学术假设可能与用户需求不符。作者提出展望：让群体成员通过聊天界面交流，由基于生成式 AI（如 ChatGPT）的 AI 智能体辅助决策过程，以实现更自然的交互并促进群体推荐系统的实际普及。
正文 · 原文
Abstract:More than twenty-five years ago, early ideas emerged on how to design systems that provide recommendations to groups of users rather than individuals. Since then, a wide range of algorithmic approaches has been proposed to elicit individual preferences, aggregate them, and generate group recommendations. However, despite this substantial body of work, relatively few examples of real-world group recommender systems are in use. This observation invites reflection on the assumptions of the academic research, particularly regarding how inter-group communication unfolds and how recommendation-supported decisions should be made. In this essay, we suggest that some of these assumptions and corresponding system designs may not fully align with users' needs or expectations. We therefore outline a forward-looking perspective that explores how insights from group-decision making research and recent advances in Generative AI, including systems such as ChatGPT, could better inform the design of group recommender systems. As one possible direction, we consider settings in which human group members interact and exchange information through a chat based interface, while an AI-based agent supports the decision-making process. Such an approach may contribute to design more natural group and system interactions, and could help facilitate a broader adoption of group recommender systems in practice.
| Comments: | Submitted for publication |
| Subjects: | Information Retrieval (cs.IR); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2507.00535 [cs.IR] |
| (or arXiv:2507.00535v3 [cs.IR] for this version) | |
| https://doi.org/10.48550/arXiv.2507.00535 arXiv-issued DOI via DataCite |
Submission history
From: Dietmar Jannach [view email]
[v1]
Tue, 1 Jul 2025 07:56:37 UTC (164 KB)
[v2]
Mon, 3 Aug 2026 09:27:30 UTC (170 KB)
[v3]
Thu, 29 Oct 2026 07:28:06 UTC (3,729 KB)
来源：arXiv cs.AI · arxiv.org