TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems.
Peiyan ZhangYuchen YanXi ZhangChaozhuo LiSenzhang WangFeiran HuangSunghun KimPublished in: SIGIR (2024)
Keyphrases
- recommender systems
- neural network
- collaborative filtering
- user modelling
- random walk
- collective intelligence
- collaborative learning
- pattern recognition
- graph representation
- back propagation
- structured data
- neural network model
- graph theory
- neural nets
- graph structure
- artificial neural networks
- graph model
- trust aware
- power consumption
- cold start problem
- user profiling
- information overload
- user profiles
- directed acyclic graph
- multi layer
- user model
- user modeling
- graph theoretic
- directed graph
- self organizing maps
- user preferences
- collaborative recommender systems
- graph based algorithm
- graph matching
- spanning tree
- bipartite graph
- matrix factorization
- multilayer perceptron
- feed forward
- radial basis function
- fault diagnosis
- genetic algorithm
- information retrieval