Understanding Recommendation Ranking: Definition, Decomposition, and Modeling
This article introduces recommendation ranking, breaks down its components, explains how to build ranking models, and provides additional insights, while also presenting the author's background and related job opportunities in the e‑commerce recommendation field.
The article, authored by Yao Kaifei, head of recommendation algorithms at Club Factory, begins with an overview of recommendation ranking, explaining its purpose in e‑commerce and video platforms.
It then dissects the ranking process into key sub‑tasks, illustrating each step with visual diagrams.
Subsequently, the piece describes how to construct ranking models, covering feature engineering, model selection, and evaluation, again supported by illustrative images.
Additional miscellaneous topics are presented in a final section.
Author information is provided, highlighting his experience at Alibaba and academic background from Shanghai Jiao Tong University.
The article concludes with a job referral for algorithm and development engineers at Club Factory, including contact details and a brief company introduction.
Supplementary links to related articles on recommendation system measurement, evaluation, and data considerations are also listed.
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