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- W4288095477 abstract "Recent research focuses beyond recommendation accuracy, towards human factors that influence the acceptance of recommendations, such as user satisfaction, trust, transparency and sense of control.We present a generic interactive recommender framework that can add interaction functionalities to non-interactive recommender systems.We take advantage of dialogue systems to interact with the user and we design a middleware layer to provide the interaction functions, such as providing explanations for the recommendations, managing users preferences learnt from dialogue, preference elicitation and refining recommendations based on learnt preferences." @default.
- W4288095477 created "2022-07-28" @default.
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- W4288095477 date "2019-10-03" @default.
- W4288095477 modified "2023-10-06" @default.
- W4288095477 title "IRF: Interactive Recommendation through Dialogue" @default.
- W4288095477 doi "https://doi.org/10.48550/arxiv.1910.03040" @default.
- W4288095477 hasPublicationYear "2019" @default.
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