A spectral approach to clustering numerical vectors as nodes in a network.
Motoki ShigaIchigaku TakigawaHiroshi MamitsukaPublished in: Pattern Recognit. (2011)
Keyphrases
- network structure
- clustering algorithm
- centrality measures
- small world
- binary vectors
- clustering method
- k means
- intermediate nodes
- network topologies
- information networks
- network nodes
- origin destination
- complex networks
- computer networks
- neighboring nodes
- cluster analysis
- neighborhood information
- categorical data
- spectral methods
- sparsely connected
- fully connected
- real world networks
- strongly connected
- network connectivity
- unstructured peer to peer
- spectral analysis
- path length
- document clustering
- data objects
- spanning tree
- peer to peer
- shortest path
- data points
- spectral clustering
- propagation model
- network analysis
- network model
- minimum cost
- hidden nodes
- heterogeneous networks
- local area network
- wireless sensor networks
- mobile nodes
- social networks
- scale free