GLIMG: Global and local item graphs for top-N recommender systems.
Zhuoyi LinLei FengRui YinChi XuChee Keong KwohPublished in: Inf. Sci. (2021)
Keyphrases
- recommender systems
- cold start problem
- collaborative filtering
- user preferences
- personalized recommendation
- recommendation algorithms
- cold start
- item based collaborative filtering
- user ratings
- matrix factorization
- graph matching
- item recommendation
- global information
- graph theoretic
- rating prediction
- active user
- information filtering
- random graphs
- graph representation
- user profiling
- graph databases
- information overload
- latent factor models
- graph structure
- graph theory
- directed graph
- hybrid recommendation