ITGNN: Item Transition Attentive Graph Neural Network for Session-Based Recommendation.
Chao ZhangZhao LiTong ChenYiming ZhanXiuhao ZhaoPublished in: ICEA (2021)
Keyphrases
- neural network
- user preferences
- personalized recommendation
- cold start problem
- graph structure
- collaborative filtering
- weighted graph
- graph representation
- item recommendation
- pattern recognition
- recommender systems
- latent factor models
- directed graph
- graph theory
- recommendation systems
- connected components
- long tail
- cold start
- artificial neural networks
- user ratings
- graph model
- collaborative filtering recommendation algorithm
- fuzzy logic
- neural network model
- genetic algorithm
- neural nets
- neural network is trained
- random walk
- back propagation
- self organizing maps
- tag recommendation
- eye movements
- recommendation algorithms
- network architecture
- recurrent neural networks
- feed forward
- spanning tree
- graph databases
- graph matching
- graph mining
- prediction model
- user interests
- knn
- making recommendations
- heterogeneous social networks
- associative memory