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Deep learning approach to mitigate the cold-start problem in textual items recommendations
Deep learning approach to mitigate the cold-start problem in textual items recommendations
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机译:深入学习方法,以减轻文本项目建议的冷启动问题
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摘要
A method for mitigating cold starts in recommendations includes receiving a request that identifies a requested page and identifying a content vector of the requested page. The content vector is generated based on providing text of the requested page to a neural network text encoder. The method further includes selecting, based on a rank engine and the content vector, a link to a cold start page that does not satisfy a threshold level of interaction data. The rank engine ranks the selected link above a second link to a warm page that does satisfy the threshold level of the interaction data. The method further includes presenting the requested page with the selected link.
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