Finding What Users Look for by Attribute-Aware Personalized Item Comparison in Relevant Recommendation.
Rui MaDike SunJincheng XuJingsong YuanJiandong ZhangPublished in: WWW (Companion Volume) (2024)
Keyphrases
- personalized recommendation
- recommender systems
- personal preferences
- collaborative filtering
- cold start problem
- user profiles
- user preferences
- recommendation algorithms
- personalized services
- user interests
- recommendation systems
- cold start
- user context
- user specific
- personalized information
- product recommendation
- user feedback
- user modeling
- item recommendation
- individual user
- user oriented
- information overload
- user ratings
- online dating
- item based collaborative filtering
- active user
- user profiling
- user model
- collaborative recommendation
- long tail
- rating prediction
- providing personalized
- making recommendations
- user centered
- latent factor models
- user similarity
- hybrid recommendation
- travel information
- user interface
- data sparsity
- user interaction
- information services
- information filtering
- implicit feedback
- social tags
- helping users
- user requirements
- tag recommendation
- potentially relevant
- personalized search
- e learning
- user generated content
- online video
- matrix factorization
- web content
- user experience
- user behavior
- attribute values
- context aware
- social media