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English(EN) Revisiting N2DCG: An Empirically Grounded Reformulation of Carousel Recommendation Evaluation

新研究应对轮播推荐评估挑战 · 已追踪 2 个来源

作者 PulseAugur 编辑部 · [2 个来源] ·

两篇新提交至 arXiv 的研究论文解决了轮播界面中推荐系统评估的挑战。第一篇论文专注于开发一个点击建模框架，该框架考虑了轮播独特的二维布局，旨在改进从日志交互数据进行的策略评估。第二篇论文重新审视并重构了 N2DCG 指标，提出了改进建议，以更好地反映用户浏览行为，并基于实证数据和眼动追踪研究准确预测轮播布局的性能。 AI

影响 这些论文提出了改进的轮播推荐系统评估方法，有可能在这些界面中带来更有效的用户参与和个性化内容推送。

排序理由 两篇发表在 arXiv 上的学术论文，详细介绍了评估轮播推荐系统的新方法。

在 arXiv cs.IR (Information Retrieval) 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

新研究应对轮播推荐评估挑战 · 已追踪 2 个来源

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两篇发表在 arXiv 上的学术论文，详细介绍了评估轮播推荐系统的新方法。
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报道来源 [2]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Jingwei Kang ·

    从点击模型到轮播推荐中的离线和离策略评估

    Carousel interfaces are widely used in modern recommendation systems. Unlike traditional interfaces that present a single ranked list, carousels simultaneously present several ranked lists to the user, as horizontally swipeable rows stacked on top of each other. In this design, t…

  2. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Harrie Oosterhuis ·

    重新审视N2DCG：一种基于实证的旋转推荐评估的改革重述

    Carousel interfaces have been widely used in video and music streaming services, yet it remains unclear how to properly evaluate recommender systems in these two-dimensional layouts. N2DCG has been proposed to address this gap by adapting NDCG to carousel-based recommendation, bu…

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