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The success of recommender systems often depends on their ability to understand and make use of the context of the recommendation request. Significant research has focused on how time, location, interfaces, and a plethora of other contextual features affect recommendations. However, in using deep neural networks for recommender systems, researchers often ignore these contexts or incorporate them as ordinary features in the model.

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DOI
10.1145/3159652.3159727
OpenAlex
W2773640334
Document type
conference-paper
Language
EN
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