Item Graph Convolution Collaborative Filtering for Inductive Recommendations.
Edoardo D'AmicoKhalil MuhammadElias Z. TragosBarry SmythNeil HurleyAonghus LawlorPublished in: CoRR (2023)
Keyphrases
- collaborative filtering
- making recommendations
- recommender systems
- personalized recommendation
- user preferences
- hybrid recommendation
- cold start problem
- user ratings
- item recommendation
- cold start
- recommendation algorithms
- latent factor models
- collaborative filtering recommendation algorithm
- matrix factorization
- user similarity
- recommendation systems
- active user
- data sparsity
- collaborative filtering algorithms
- recommendation quality
- random walk
- graph structure
- online dating
- pearson correlation coefficient
- collaborative filtering recommendation
- collaborative recommendation
- machine learning
- prediction accuracy
- item based collaborative filtering
- inductive learning
- graph theory
- rating prediction
- content based filtering
- demographic information
- user item rating
- graph representation
- bipartite graph
- transfer learning
- product recommendation
- graph model
- directed acyclic graph
- directed graph
- structured data
- deal with information overload
- image processing
- tag recommendation
- graph mining
- user interests
- inductive logic programming
- user behavior