The flow of information through active users in online social networks (OSNs) plays a major
role in forming natural social groups, popularly known as communities. Although structural …

This paper presents two different versions of a new internal index for clustering validation
using graphs. These graphs capture the structural characteristics of each cluster. In this way …

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 …

Creating the proper player profile in training is crucial for athlete development. Although
there is a great number of studies concerning this subject, there is no solution that would …

Graph clustering has attracted many interests in recent years, with numerous applications
ranging from the clustering of computer networks to the detection of social communities. It …

Outlier detection plays a crucial role in the field of data mining and machine learning.
Despite the diverse range of outlier detection algorithms, most still face two main …

Clustering analysis is a powerful tool for discovering potential knowledge in datasets.
However, numerous existing clustering algorithms suffer from heavy reliance on parameter …

Abstract Information exchange among individuals is one of the key factors leading to
formation of modular structures in social networks, often referred as communities. In this …

Measuring graph clustering quality remains an open problem. Here, we introduce three
statistical measures to address the problem. We empirically explore their behavior under a …

Complex networks have been widely used to model complex systems composed of
interacting entities. It is possible to recommend new relationships between entities …