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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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發(fā)表于 2025-3-23 13:41:46 | 只看該作者
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發(fā)表于 2025-3-23 15:46:25 | 只看該作者
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發(fā)表于 2025-3-23 21:08:20 | 只看該作者
SpringerBriefs in Computer Sciencehttp://image.papertrans.cn/c/image/236884.jpg
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發(fā)表于 2025-3-23 22:48:39 | 只看該作者
https://doi.org/10.1007/978-981-10-5373-3Collaborative prediction; Hierarchical representation; Contextual representation; Contextual informatio
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發(fā)表于 2025-3-24 04:01:14 | 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.
16#
發(fā)表于 2025-3-24 09:29:29 | 只看該作者
Synthesis Lectures on Visualizationhere 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
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發(fā)表于 2025-3-24 11:43:32 | 只看該作者
Synthesis Lectures on Visualization operation represents each context value with a latent vector and models the contextual information as a semantic operation on the user and item. Besides, the contextual operating tensor is used to capture the common semantic effects of contexts. This chapter introduces notations and fundamental con
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發(fā)表于 2025-3-24 18:43:23 | 只看該作者
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發(fā)表于 2025-3-24 22:44:29 | 只看該作者
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