Unraveling Multifaceted User Preferences on Digital Platforms: A Bayesian Deep-Learning Approach
提出一种贝叶斯深度学习模型，捕捉数字平台上用户活动的多面性和时变性，在平台和个体层面生成可解释的动态偏好估计。
This paper proposes a Bayesian deep-learning model that captures multifaceted, time-varying user activities on digital platforms, yielding interpretable and dynamic preference estimations at the platform and individual levels.