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On component interactions in two-stage recommender systems. (arXiv:2106.14979v3 [cs.IR] UPDATED)
Jan. 14, 2022, 2:11 a.m. | Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus
cs.LG updates on arXiv.org arxiv.org
Thanks to their scalability, two-stage recommenders are used by many of
today's largest online platforms, including YouTube, LinkedIn, and Pinterest.
These systems produce recommendations in two steps: (i) multiple nominators,
tuned for low prediction latency, preselect a small subset of candidates from
the whole item pool; (ii) a slower but more accurate ranker further narrows
down the nominated items, and serves to the user. Despite their popularity, the
literature on two-stage recommenders is relatively scarce, and the algorithms
are often …
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