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    Search, retrieval & recommendation· 2016

    Deep Neural Networks for YouTube Recommendations

    Paul Covington (first author) · 2016

    Read the original

    DOI 10.1145/2959100.2959190OpenAlex W2512971201

    On the reading lists

    Why it matters

    Established the influential deep candidate-generation and ranking architecture for industrial recommenders.

    Condensed from the expert lists' notes.

    Reading it

    Difficulty: Introductory

    Read this first: neural network basics (backpropagation); Amazon.com Recommendations (item-to-item).

    The record

    First released
    2016 (from OpenAlex)
    Citations
    3,537 citations, as counted by OpenAlex (CC0)
    Named by
    both expert lists
    Score
    0.609 · computed rank 142 · consensus 0.79, must-read 1, citations percentile 0.778 (2010s · retrieval), awards 0, existing lists 0. Method

    Editor's notes

    • Readability check: pass: Short industrial paper on recommendation at scale. (AI draft (Claude), not yet reviewed, 2026-10-29)

    Data sources

    Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.