Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks.
Yabo NiDan OuShichen LiuXiang LiWenwu OuAnxiang ZengLuo SiPublished in: KDD (2018)
Keyphrases
- multiple tasks
- multiple users
- collaborative filtering
- user feedback
- multi task learning
- user interface
- learning process
- end users
- user interaction
- learning algorithm
- query formulation
- multi task
- user oriented
- recommender systems
- computer users
- supervised learning
- user studies
- user groups
- novice users
- reinforcement learning
- information overload
- human users
- user satisfaction
- user experience
- user queries
- active learning
- location information
- user centered
- helping users
- external representations