Link prediction is a paradigmatic problem in network science, which aims at estimating the
existence likelihoods of nonobserved links, based on known topology. After a brief …

The hacker group identification is an important pre-work for tasks such as hacking tracing,
criminal portraits. The current hacker identification mainly relies on fingerprints and clue …

Graph embedding is a transformation of nodes of a network into a set of vectors. A good
embedding should capture the underlying graph topology and structure, node-to-node …

This book draws a broad-stroke, panoramic picture of the State of the Art (SoTA) of the
research in generative methods for the analysis of social media data. It fills a void, as the …

Data mining is a good way to find the relationship between raw data and predict the target
we want which is also widely used in different field nowadays. In this project, we implement …

In recent years, the growing interconnection of entities through various links has led to the
emergence of a unique characteristic: the structure of multiplex networked industrial chains …

In this paper, we propose a framework that uses the theory and techniques of (Social)
Network Analysis to investigate the learned representations of a Graph Neural Network …

Employee turnover poses a critical challenge that affects many organizations globally.
Although advanced machine learning algorithms offer promising solutions for predicting …

Large-scale knowledge graphs with billions of nodes and edges are increasingly common in
many domains. Such graphs often exceed the capacity of the systems storing the graphs in a …

Networks provide an understandable and, in the case of small size, visualizable
representation of data, which allows us to obtain essential information about the …