Deep Neural Networks for Youtube Recommendations

Paul Covington, Jay Adams

Abstract: YouTube represents one of the largest scale and most sophis- ticated industrial recommendation systems in existence. In this paper, we describe the system at a high level and fo- cus 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 maintain-ing a massive recommendation system with enormous user- facing impact.