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New KuaiLive dataset offers real-time insights for live streaming recommendations

Researchers have introduced KuaiLive, a new real-time dataset designed to advance research in live streaming recommendation systems. Collected from Kuaishou, a major Chinese live streaming platform, the dataset spans 21 days and includes interaction logs from over 23,000 users and 450,000 streamers. KuaiLive features precise timestamps, diverse interaction types like clicks and gifts, and rich contextual information, aiming to provide a more realistic environment for developing and evaluating recommendation algorithms. AI

Summary written by gemini-2.5-flash-lite from 1 source. How we write summaries →

IMPACT Provides a benchmark dataset to improve live streaming recommendation algorithms and user engagement strategies.

RANK_REASON Release of a new academic dataset for a specific AI task.

Read on arXiv cs.AI →

COVERAGE [1]

  1. arXiv cs.AI TIER_1 · Changle Qu, Sunhao Dai, Ke Guo, Xiao Zhang, Liqin Zhao, Shijun Wang, Yannan Niu, Lantao Hu, Han Li, Jun Xu ·

    KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation

    arXiv:2508.05633v2 Announce Type: replace-cross Abstract: Live streaming platforms have become a dominant form of online content consumption, offering dynamically evolving content, real-time interactions, and highly engaging user experiences. These unique characteristics introduc…