RecSys 2016: Paper Session 6 - Deep Neural Networks for YouTube Recommendations

Автор: ACM RecSys

Загружено: 2017-03-30

Просмотров: 18801

Описание:

Paul Covington, Jay Adams, Emre Sargin
https://doi.org/10.1145/2959100.2959190
YouTube represents one of the largest scale and most sophisticated industrial recommendation systems in existence. In this paper, we describe the system at a high level and focus on the dramatic performance improvements brought by deep learning. The paper is split according to the classic two-stage information retrieval dichotomy: first, we detail a deep candidate generation model and then describe a separate deep ranking model. We also provide practical lessons and insights derived from designing, iterating and maintaining a massive recommendation system with enormous user-facing impact.

RecSys 2016: Paper Session 6 - Deep Neural Networks for YouTube Recommendations

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