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Method for cold start of a multi-armed bandit in a recommender system
Method for cold start of a multi-armed bandit in a recommender system
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机译:推荐系统中多臂匪的冷启动方法
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摘要
A method performed by a recommender system to recommend items to a new user includes calculating reward estimates from multiple multi-armed bandit models of a user and her social network friends. The new user's social network friends have multi-armed bandit models that are well established. The mixed multi-armed bandit estimates are processed to select the arm that maximizes the estimated reward to the new user. The multi-armed bandit arm of the greatest reward estimate is played and the new user responds by providing feedback so that the new user's multi-armed bandit model is updated as time progresses.
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