GLIMG: Global and Local Item Graphs for Top-N Recommender Systems.
Zhuoyi LinLei FengRui YinChi XuChee-Keong KwohPublished in: CoRR (2020)
Keyphrases
- recommender systems
- user preferences
- cold start problem
- collaborative filtering
- personalized recommendation
- recommendation algorithms
- hybrid recommendation
- item based collaborative filtering
- active user
- user ratings
- item recommendation
- cold start
- graph theoretic
- graph matching
- social networks
- graph theory
- rating prediction
- matrix factorization
- global information
- graph databases
- bipartite graph
- directed graph
- structured data
- latent factor models
- graph representation
- contextual information
- user interests