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- W4226304833 abstract "Recommender systems aim to help users find relevant items more quickly by providing personalized recommendations. Explanations in recommender systems help users understand why such recommendations have been generated, which in turn makes the system more transparent and promotes users’ trust and satisfaction. In recent years, explaining recommendations has drawn increasing attention from both academia and from industry. In this paper, we present a user study to investigate context-aware explanations in recommender systems. In particular, we build a web-based questionnaire that is able to interact with users: generating and explaining recommendations. With this questionnaire, we investigate the effects of context-aware explanations in terms of efficiency, effectiveness, persuasiveness, satisfaction, trust and transparency through a user study." @default.
- W4226304833 created "2022-05-05" @default.
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- W4226304833 date "2022-01-01" @default.
- W4226304833 modified "2023-10-18" @default.
- W4226304833 title "Context-Aware Explanations in Recommender Systems" @default.
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- W4226304833 doi "https://doi.org/10.1007/978-3-030-98531-8_8" @default.
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