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Titlebook: Context-Aware Collaborative Prediction; Shu Wu,Qiang Liu,Tieniu Tan Book 2017 The Author(s) 2017 Collaborative prediction.Hierarchical rep

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21#
發(fā)表于 2025-3-25 04:43:11 | 只看該作者
22#
發(fā)表于 2025-3-25 08:42:03 | 只看該作者
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發(fā)表于 2025-3-25 14:17:49 | 只看該作者
Dar’ya Guarnera,Giuseppe Claudio Guarneraware collaborative prediction and point out some limitations of the conventional methods. Finally, we introduce the tasks of collaborative prediction, on which we will compare the performance of our methods and conventional methods.
24#
發(fā)表于 2025-3-25 15:54:59 | 只看該作者
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發(fā)表于 2025-3-25 22:23:26 | 只看該作者
Performance of Different Collaborative Prediction Tasks, impact of parameters are also analyzed. Last but not the least, we visualize the representations in latent collaborative retrieval and find some interesting observations on context representations and context weights.
26#
發(fā)表于 2025-3-26 00:39:04 | 只看該作者
27#
發(fā)表于 2025-3-26 08:18:49 | 只看該作者
Introduction,ware collaborative prediction and point out some limitations of the conventional methods. Finally, we introduce the tasks of collaborative prediction, on which we will compare the performance of our methods and conventional methods.
28#
發(fā)表于 2025-3-26 12:20:46 | 只看該作者
Context-Aware Collaborative Prediction,here are two general ways to integrate contexts with collaborative prediction: contextual filtering and contextual modeling. Contextual filtering uses contexts to select data and adjust the result, while contextual modeling takes contexts into the model construction. Currently, the most effective co
29#
發(fā)表于 2025-3-26 15:01:10 | 只看該作者
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發(fā)表于 2025-3-26 19:55:46 | 只看該作者
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