MhSa-GRU: combining user's dynamic preferences and items' correlation to augment sequence recommendation.
Yongrui DuanPeng LiuYusheng LuPublished in: J. Intell. Inf. Syst. (2023)
Keyphrases
- user preferences
- recommender systems
- collaborative filtering
- personalized services
- recommendation systems
- individual user
- user feedback
- user profiles
- user behavior
- decision making
- personal preferences
- personal interests
- user interaction
- collaborative recommendation
- personalized recommendation
- user satisfaction
- dynamic environments
- making recommendations
- user modeling
- information retrieval
- explicit feedback
- dynamically generated
- long tail
- web page recommendation
- user specific
- user profiling
- user requirements
- user interests
- recommendation algorithms
- cold start
- user context
- helping users
- information overload
- individual preferences
- user model
- preference models
- context aware
- customer preferences
- end users
- user interface