Networks can describe the structure of a wide variety of complex systems by specifying
which pairs of entities in the system are connected. While such pairwise representations are …

Mining patterns is a core task in data analysis and, beyond issues of efficient enumeration,
the selection of patterns constitutes a major challenge. The Minimum Description Length …

Community detection is a commonly used technique for identifying groups in a network
based on similarities in connectivity patterns. To facilitate community detection in large …

Motivated by the problem of human-trafficking, where it is often observed that criminal
organizations are linked and behave similarly over time, we introduce the problem of …

To compress a graph, some methods rely on finding highly compressible structures, such as
very dense subgraphs, and encode a graph by listing these structures compressed …

Pairwise temporal interactions between entities can be represented as temporal networks,
which code the propagation of processes such as epidemic spreading or information …

Several graph compression approaches rely on finding dense structures such as cliques or
quasi-cliques which are simple to encode, ie, they are defined by the set of their vertices …

Consumers lead rich digital lives, and demand real-time personalized service and delivery
of content. Brands and companies are continuously calibrating their strategies to win over …

Dense subgraphs convey important information and insights about a graph structure.
Several applications, such as graph visualization, graph summarization, and complex …

The comprehension of social network phenomena is closely related to data visualization.
However, even with only hundreds of nodes, the visualization of dense networks is usually …