Network Embedding Based on Biased Random Walk for Community Detection in Attributed Networks.
Kun GuoZizheng ZhaoZhiyong YuWenzhong GuoRonghua LinYong TangLing WuPublished in: IEEE Trans. Comput. Soc. Syst. (2023)
Keyphrases
- random walk
- community detection
- link prediction
- network analysis
- complex networks
- real world networks
- community structure
- bipartite networks
- community detection algorithms
- biological networks
- network structure
- overlapping communities
- information diffusion
- information networks
- graph mining
- social networks
- hyper graph
- bipartite graph
- cohesive subgroups
- social network data
- markov chain
- heterogeneous networks
- directed graph
- social network analysis
- graph clustering
- citation networks
- markov random walk
- social graph
- link structure
- scale free
- real world social networks
- average degree
- transition probability matrix
- link analysis
- networked data
- label propagation
- nodes of a graph
- graph laplacian