Improving Recommendation Diversity Across Users by Reducing Frequently Recommended Items.
Seiki MiyamotoTakumi ZamamiHayato YamanaPublished in: IEEE BigData (2018)
Keyphrases
- recommender systems
- collaborative filtering
- online dating
- recommendation systems
- information overload
- user feedback
- user interface
- recommendation algorithms
- cold start problem
- social context
- helping users
- product recommendation
- data sparsity
- user interaction
- multiple users
- matrix factorization
- user profiles
- content based filtering
- query recommendation
- active user
- personalized recommender systems
- user requirements
- user ratings
- user profiling
- user satisfaction
- personalized services
- user preferences
- location based social networks
- travel information