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- W2148933855 abstract "This paper studies result diversification in collaborative filtering. We argue that the diversification level in a recommendation list should be adapted to the target users' individual situations and needs. Different users may have different ranges of interests -- the preference of a highly focused user might include only few topics, whereas that of the user with broad interests may encompass a wide range of topics. Thus, the recommended items should be diversified according to the interest range of the target user. Such an adaptation is also required due to the fact that the uncertainty of the estimated user preference model may vary significantly between users. To reduce the risk of the recommendation, we should take the difference of the uncertainty into account as well." @default.
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- W2148933855 date "2012-08-12" @default.
- W2148933855 modified "2023-10-17" @default.
- W2148933855 title "Adaptive diversification of recommendation results via latent factor portfolio" @default.
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- W2148933855 doi "https://doi.org/10.1145/2348283.2348310" @default.
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