Unsupervised Learning for Identifying High Eigenvector Centrality Nodes: A Graph Neural Network Approach.
Appan RakaraddiMahardhika PratamaPublished in: IEEE BigData (2021)
Keyphrases
- unsupervised learning
- neural network
- adjacency matrix
- directed graph
- graph structure
- betweenness centrality
- weighted graph
- graph representation
- undirected graph
- complex networks
- graph structures
- network structure
- shortest path
- graph matching
- edge weights
- nodes of a graph
- graph theory
- random graphs
- social network analysis
- supervised learning
- artificial neural networks
- back propagation
- structured data
- graph connectivity
- graph model
- centrality measures
- spectral methods
- strongly connected
- fully connected
- neural nets
- average degree
- graph partitioning
- spanning tree
- bipartite graph
- singular value decomposition
- covariance matrix
- linear combination
- random walk
- network analysis
- neural network model
- data clustering
- expectation maximization
- terrorist networks
- text classification
- principal component analysis
- object recognition
- reinforcement learning
- machine learning