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LiveForesighter: Generating Future Information for Live-Streaming Recommendations at Kuaishou
February 10, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Yucheng Lu, Jiangxia Cao, Xu Kuan, Wei Cheng, Wei Jiang, Jiaming Zhang, Yang Shuang, Liu Zhaojie, Liyin Hong
arXiv ID
2502.06557
Category
cs.IR: Information Retrieval
Citations
8
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Live-streaming, as a new-generation media to connect users and authors, has attracted a lot of attention and experienced rapid growth in recent years. Compared with the content-static short-video recommendation, the live-streaming recommendation faces more challenges in giving our users a satisfactory experience: (1) Live-streaming content is dynamically ever-changing along time. (2) valuable behaviors (e.g., send digital-gift, buy products) always require users to watch for a long-time (>10 min). Combining the two attributes, here raising a challenging question for live-streaming recommendation: How to discover the live-streamings that the content user is interested in at the current moment, and further a period in the future?
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