Graph representation learning has re-emerged as a fascinating research topic due to the
successful application of graph convolutional networks (GCNs) for graphs and inspires …

Non-ferrous metals are indispensable industrial materials and strategic supports of national
economic development. The price forecasting of non-ferrous metals is critical for investors …

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 epidemic diseases have been threatening to human health, and it is of high importance
to understand the properties of epidemic propagation among the population will help us to …

With the explosion of social media networks, many modern applications are concerning
about people's connections, which leads to the so-called social computing. An elusive …

Community structure division is a crucial problem in the field of network data analysis.
Algorithms based on Markov chains are easy to use and provide promising solutions for …

Identifying influential nodes in complex networks is still an open issue. A number of
measures have been proposed to improve the validity and accuracy of the influential nodes …

In recent years, a new Internet-based unsecured credit model, peer-to-peer (P2P) lending, is
flourishing and has become a successful complement to the traditional credit business …

Community structure is the most significant attribute of networks, which is often identified to
help discover the underlying organization of networks. Currently, nonnegative matrix …

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 …