Rapid technology integration causes a high dimensional time series data accumulation in
multiple domains and applying the classical data mining tools and techniques becomes a …

What do football passes and financial transactions have in common? Both are networked
walk processes that we can observe, where records take the form of timestamped events …

Positive and negative relations play an essential role in human behavior and shape the
communities we live in. Despite their importance, data about signed relations is rare and …

Community smells are negative patterns in software development teams' interactions that
impede their ability to successfully create software. Examples are team members working in …

The structure of complex networks can be characterized by counting and analysing network
motifs. Motifs are small graph structures that occur repeatedly in a network, such as triangles …

Apart from nodes and links, for many networked systems, we have access to data on paths,
ie, collections of temporally ordered variable-length node sequences that are constrained by …

Graph and network models are essential for data science applications in computer science,
social sciences, and life sciences. They help to detect patterns in data on dyadic relations …

An evolving graph maintains the history of changes of graph topology and attribute values
over time. Such a graph has a specific temporal and structural resolution. It is often useful to …

The maritime shipping network is the backbone of global trade. Data about the movement of
cargo through this network comes in various forms, from ship-level Automatic Identification …

Higher-order graph neural networks (HOGNNs) are an important class of GNN models that
harness polyadic relations between vertices beyond plain edges. They have been used to …