In this paper, we present a novel graph data model to analyze eating habits and physical
activities of a large number of persons, aiming at automatically detect groups of users …

The study of community detection in networks has drawn great attention in recent years. To
find communities and to understand community semantics, both network topology and …

This paper proposes a meaningful and effective extension of the celebrated K-means
algorithm to detect communities in feature-rich networks, due to our assumption of non …

The human brain can be regarded as a complex network with interacting connections
between brain regions. Complex brain network analyses have been widely applied to …

Community detection is essential for identifying cohesive groups in complex networks.
Artificial benchmarks are critical for evaluating community detection algorithms, offering …

Complex systems surround us in our everyday lives and their understanding can bring
crucial insights into many fields. These systems consist of components (also known as …