Graph Sampling Approach for Reducing Computational Complexity of Large-Scale Social Network.
Andry AlamsyahYahya PeranginanginIntan Muchtadi-AlamsyahBudi Rahardjo KuspriyantoPublished in: CoRR (2021)
Keyphrases
- computational complexity
- social networks
- massive graphs
- social graphs
- small scale
- community discovery
- social network analysis
- graph theory
- graph mining algorithms
- graph representation
- degree distribution
- heterogeneous social networks
- decision problems
- memory requirements
- special case
- weighted graph
- random walk
- high computational complexity
- clustering coefficient
- random sampling
- graph structure
- np complete
- bipartite graph
- directed graph
- graph matching
- graph model
- connected components
- network structure
- graph theoretic
- information diffusion
- real world social networks
- overlapping communities
- adjacency matrix
- monte carlo
- sampling algorithm
- web graph
- graph partitioning
- bit rate
- random graphs
- small world
- social media
- graph mining
- betweenness centrality
- np hard
- social networking
- online social networks
- active learning