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• W3201632862 abstract "Live-streaming platforms broadcast user-generated video in real-time. Recommendation on these platforms shares similarities with traditional settings, such as a large volume of heterogeneous content and highly skewed interaction distributions. However, several challenges must be overcome to adapt recommendation algorithms to live-streaming platforms: first, content availability is dynamic which restricts users to choose from only a subset of items at any given time; during training and inference we must carefully handle this factor in order to properly account for such signals, where ‘non-interactions’ reflect availability as much as implicit preference. Streamers are also fundamentally different from ‘items’ in traditional settings: repeat consumption of specific channels plays a significant role, though the content itself is fundamentally ephemeral." @default.
• W3201632862 created "2021-09-27" @default.
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• W3201632862 date "2021-09-13" @default.
• W3201632862 modified "2023-10-06" @default.
• W3201632862 title "Recommendation on Live-Streaming Platforms: Dynamic Availability and Repeat Consumption" @default.
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• W3201632862 doi "https://doi.org/10.1145/3460231.3474267" @default.
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