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- W25808122 abstract "To follow the dynamicity of the user’s content, researchers have recently started to model interactions between users and the Context-Aware Recommender Systems (CARS) as a bandit problem where the system needs to deal with exploration and exploitation dilemma. In this sense, we propose to study the freshness of the user’s content in CARS through the bandit problem. We introduce in this paper an algorithm named Freshness-Aware Thompson Sampling (FA-TS) that manages the recommendation of fresh document according to the user’s risk of the situation. The intensive evaluation and the detailed analysis of the experimental results reveals several important discoveries in the exploration/exploitation (exr/exp) behaviour." @default.
- W25808122 created "2016-06-24" @default.
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- W25808122 date "2014-01-01" @default.
- W25808122 modified "2023-09-27" @default.
- W25808122 title "Freshness-Aware Thompson Sampling" @default.
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- W25808122 doi "https://doi.org/10.1007/978-3-319-12643-2_46" @default.
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