2 the assembled benchmark suite, the challenges create a reproducible picture of the state
of the art in the area under consideration. This helps to foster an effective technology transfer …

The mode of-core and its hierarchical decomposition have been applied in many areas,
such as sociology, the world wide web, and biology. Algorithms on related studies often …

Clustering addresses the problem of finding homogeneous and well-separated subsets,
called clusters, from a set of given data points. In addition to the points themselves, in many …

Many algorithms have been developed to detect communities in networks. The success of
these developed algorithms varies according to the types of networks. A community …

Data are often represented as graphs. Many common tasks in data science are based on
distances between entities. While some data science methodologies natively take graphs as …

Time series segmentation is a crucial area of research in time series analysis as it can
reveal meaningful patterns or segments hidden within time series data. In this paper, we …

The mode of k-core and its hierarchical decomposition have been applied in many areas,
such as sociology, the world wide web, and biology. Algorithms on related studies often …

Network community detection often relies on optimizing partition quality functions, like
modularity. This optimization appears to be a complex problem traditionally relying on …

The detection of community structure is a widely accepted means of investigating the
principles governing biological systems. Recent efforts are exploring ways in which multiple …

We introduce graph clustering quality measures based on comparisons of global, intra-and
inter-cluster densities, an accompanying statistical significance test and a step-by-step …