With the rapid development of information technologies, various big graphs are prevalent in
many real applications (eg, social media and knowledge bases). An important component of …

Distributed processing of large-scale graph data has many practical applications and has
been widely studied. In recent years, a lot of distributed graph processing frameworks and …

Identifying influential spreaders is an important issue in understanding the dynamics of
information diffusion in complex networks. The k-shell index, which is the topological …

In complex networks, each node has some unique characteristics that define the importance
of the node based on the given application-specific context. These characteristics can be …

With the rapid development of science and technology, the world is becoming increasingly
connected. The following dire need for understanding both the relationships amongst …

The core decomposition of networks has attracted significant attention due to its numerous
applications in real-life problems. Simply stated, the core decomposition of a network …

Studying the topology of a network is critical to inferring underlying dynamics such as
tolerance to failure, group behavior and spreading patterns. k-core decomposition is a well …

Densest subgraph discovery (DSD) is a fundamental problem in graph mining. It has been
studied for decades, and is widely used in various areas, including network science …

Existing graph-processing frameworks let users develop efficient implementations for many
graph problems, but none of them support efficiently bucketing vertices, which is needed for …

The k-core decomposition in a graph is a fundamental problem for social network analysis.
The problem of k-core decomposition is to calculate the core number for every node in a …