Methodologies for Improving Modern Industrial Recommender Systems
Shusen Wang
Recommender system (RS) is an established technology with successful
applications in social media, e-commerce, entertainment, and more. RSs are
indeed key to the success of many popular APPs, such as YouTube, Tik Tok,
Xiaohongshu, Bilibili, and others. This paper explores the methodology for
improving modern industrial RSs. It is written for experienced RS engineers who
are diligently working to improve their key performance indicators, such as
retention and duration. The experiences shared in this paper have been tested
in some real industrial RSs and are likely to be generalized to other RSs as
well. Most contents in this paper are industry experience without publicly
available references.