平衡新闻推荐的准确率与编辑价值，提升推荐系统责任感。
RecSys Challenge 2024: Balancing Accuracy and Editorial Values in News Recommendations
- 结合用户行为与新闻议程建模，捕捉动态兴趣变化。
- 引入编辑价值观评估指标，衡量推荐对新闻生态的影响。
- 适合关注负责任推荐、新闻平台算法设计的研究者。
RecSys Challenge 2024 致力于推进新闻推荐技术，解决其在实际应用中面临的技术与规范性挑战。本文介绍该挑战的目标、问题设定及由丹麦媒体集团 Ekstra Bladet 与 JP/Politikens Media Group 提供的数据集。挑战聚焦新闻推荐的独特性：基于用户行为建模偏好，考虑新闻议程对用户兴趣的影响，以及新闻内容快速过时的特性。同时，挑战纳入规范性考量，研究推荐系统对新闻传播的影响及其与编辑价值观的一致性。本文总结了挑战设置、数据集特征与评估指标，并公布获奖方案及其贡献。数据集已公开：https://recsys.eb.dk。
原文摘要 · Abstract (English)
The RecSys Challenge 2024 aims to advance news recommendation by addressing both the technical and normative challenges inherent in designing effective and responsible recommender systems for news publishing. This paper describes the challenge, including its objectives, problem setting, and the dataset provided by the Danish news publishers Ekstra Bladet and JP/Politikens Media Group ("Ekstra Bladet"). The challenge explores the unique aspects of news recommendation, such as modeling user preferences based on behavior, accounting for the influence of the news agenda on user interests, and managing the rapid decay of news items. Additionally, the challenge embraces normative complexities, investigating the effects of recommender systems on news flow and their alignment with editorial values. We summarize the challenge setup, dataset characteristics, and evaluation metrics. Finally, we announce the winners and highlight their contributions. The dataset is available at: https://recsys.eb.dk.
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