Learning transferrable parameters for long-tailed sequential user behavior modeling

• Main Authors: YIN, Jianwen, LIU, Chenghao, WANG, Weiqing, SUN, Jianling, HOI, Steven C. H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Sequential User Behavior Modeling; Long-tailed Distribution; Gradient Alignment; Adversarial Training; Databases and Information Systems; Data Science; Data Storage Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/5890; https://ink.library.smu.edu.sg/context/sis_research/article/6893/viewcontent/paper_KDD20b.pdf
• Institution: Singapore Management University

Sequential user behavior modeling plays a crucial role in online user-oriented services, such as product purchasing, news feed consumption, and online advertising. The performance of sequential modeling heavily depends on the scale and quality of historical behaviors. However, the number of user beh...