Recommender Systems over Wireless: Challenges and Opportunities
Recommender Systems over Wireless: Challenges and Opportunities
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无线推荐系统：挑战与机遇
DOI：
10.1109/itw.2018.8613423
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Devavrat Shah
中科院分区：
文献类型：
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作者：
Linqi Song;C. Fragouli;Devavrat Shah
我们考虑无线推荐系统，需要了解用户偏好（探索）并使用它们来相应地决定在带宽限制下提出（利用）最有利可图的推荐。我们提出了一种基于图的方案，利用用户端信息和编码来有效地利用和探索无线网络，并评估其性能。
We consider wireless recommender systems that need to learn the user preferences (explore) and use them to accordingly decide what are the most profitable recommendations to make (exploit), under bandwidth constraints. We propose a graph-based scheme that leverages user side information and coding to efficiently exploit and explore over wireless, and evaluate its performance.