HS-GCN: Hamming Spatial Graph Convolutional Networks for Recommendation.
Han LiuYinwei WeiJianhua YinLiqiang NiePublished in: CoRR (2023)
Keyphrases
- heterogeneous social networks
- graph representation
- small world
- network analysis
- community discovery
- spatial information
- spatial data
- spatial and temporal
- structured data
- social networks
- user preferences
- graph model
- spatio temporal
- bipartite graph
- social network analysis
- overlapping communities
- distance measure
- average degree
- graph theory
- highly connected
- dynamic networks
- fully connected
- random walk
- graph mining algorithms
- heterogeneous networks
- neighborhood graph
- social graph
- social graphs
- graph theoretic
- biological networks
- recommender systems
- collaborative filtering
- directed acyclic graph
- graph structure
- network structure
- complex networks
- connected components
- search engine
- graphical representation
- graph layout
- betweenness centrality
- degree distribution
- structural patterns
- directed graph
- graph mining
- protein interaction networks
- graph databases
- graph data