LiveForesighter: Generating Future Information for Live-Streaming Recommendations at Kuaishou

• URL: http://arxiv.org/abs/2502.06557v1
• Date: Mon, 10 Feb 2025 15:24:55 GMT
• Title: LiveForesighter: Generating Future Information for Live-Streaming Recommendations at Kuaishou
• Authors: Yucheng Lu, Jiangxia Cao, Xu Kuan, Wei Cheng, Wei Jiang, Jiaming Zhang, Yang Shuang, Liu Zhaojie, Liyin Hong,
• Abstract summary: Live-streaming is a new-generation media to connect users and authors.<n>Live-streaming content is dynamically ever-changing along time.<n>How to discover the live-streamings that the content user is interested in at the current moment?
• Score: 20.689363722025163
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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