Neighbor Interaction Aware Graph Convolution Networks for Recommendation.
Jianing SunYingxue ZhangWei GuoHuifeng GuoRuiming TangXiuqiang HeChen MaMark CoatesPublished in: SIGIR (2020)
Keyphrases
- small world
- heterogeneous social networks
- average degree
- dynamic networks
- highly connected
- collaborative filtering
- recommender systems
- human computer interaction
- edge weights
- fully connected
- social networks
- weighted graph
- complex networks
- community discovery
- network structure
- graph structures
- structured data
- graph theoretic
- scale free
- overlapping communities
- graph partitioning
- random walk
- user preferences
- graph model
- bipartite graph
- graph theory
- protein interaction networks
- image processing
- user interaction
- betweenness centrality
- path length
- network analysis
- undirected graph
- graph mining
- random graphs
- directed acyclic graph
- graph representation
- user behavior
- spanning tree
- directed edges
- convolution kernel
- social graphs
- connected components
- network size
- directed graph
- network topologies
- community detection
- back projection