Node-personalized multi-graph convolutional networks for recommendation.
Tiantian ZhouHailiang YeFeilong CaoPublished in: Neural Networks (2024)
Keyphrases
- heterogeneous social networks
- overlapping communities
- edge weights
- betweenness centrality
- graph structure
- directed graph
- social network analysis
- personalized recommendation
- social networks
- complex networks
- degree distribution
- heterogeneous networks
- graph structures
- path length
- personalized information
- neighboring nodes
- information diffusion
- densely connected
- graph theory
- community discovery
- average degree
- web personalization
- root node
- small world networks
- bipartite graph
- small world
- weighted graph
- random walk
- real world networks
- collaborative filtering
- community structure
- product recommendation
- user modeling
- information filtering
- recommender systems
- news recommendation
- nodes of a graph
- network nodes
- mobile nodes
- fully connected
- undirected graph
- recommendation systems
- network analysis
- structured data
- user profiles
- context aware
- e learning
- social graph
- personalized services
- deep learning
- recommendation algorithms
- source node
- spanning tree
- community detection
- user preferences