liyinxiao/Ranking_Papers
Papers on recommendation system / search ranking.
This is a curated collection of influential papers and talks focused on how major tech companies like Amazon, YouTube, Airbnb, and Netflix build their search ranking and recommendation systems. It includes personal notes and insights on various techniques, from deep learning models to optimization strategies. Data scientists, machine learning engineers, and product managers working on personalized user experiences will find this helpful.
Use this if you are a data scientist or engineer looking for practical insights and foundational research to build or improve recommendation engines and search ranking algorithms.
Not ideal if you are looking for ready-to-use code, an SDK, or a general introduction to machine learning concepts.
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Mar 17, 2026
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