Density peak clustering (DPC) algorithm has become a well-known clustering method
during the last decade, The research communities believe that DPC is a powerful tool …

Density peaks clustering (DPC) algorithm is a new algorithm based on density clustering
analysis, which can quickly obtain the cluster centers by drawing the decision diagram by …

Abstract In modern Online Social Networks (OSNs), the need to detect users' communities
based on their interests and social connections has became a more and more important …

Graph clustering is essential to understand the nature and behavior of real world such as
social network, technical network and transportation network. Different from the existing …

The community structure is a collection of individuals with common characteristics that
commonly exists in complex networks. The detection of community structures aids in mining …

Overlapping graph clustering is essential to understand the nature and behavior of real
complex systems including human interactions, technical systems and transportation …

Dividing a network into communities has great benefits in understanding the characteristics
of the network. The label propagation algorithm (LPA) is a fast and convenient community …

The cut-off distance of the density peaks clustering (DPC) algorithm need to be set manually;
the two local densities of the algorithm have a large difference in the clustering effect on the …

Although lots of clustering models have been proposed recently,-means and the family of
spectral clustering methods are both still drawing a lot of attention due to their simplicity and …

The emerging federated learning is a distributed machine learning paradigm which enables
training a global model on a massive number of edge devices while protecting the privacy of …