Many different approaches have been proposed for the challenging problem of visually analyzing large networks. Clustering is one of the most promising ones. In this paper, we propose a new clustering technique whose goal is producing both intracluster graphs and intercluster graph with desired topological properties. We formalize this concept in the $(X,Y)$-clustering framework, where $Y$ is the class that defines the desired topological properties of intracluster graphs and $X$ is the class that defines the desired topological properties of the intercluster graph. By exploiting this approach, hybrid visualization tools can effectively combine different node-link and matrix-based representations, allowing users to interactively explore the graph by expansion/contraction of clusters without losing their mental map. As a proof of concept, we describe the systems Visual Hybrid $(X,Y)$-clustering (VHYXY) that implements our approach and at the same time present the results in various cases of visual analysis of social networks.
COBISS.SI-ID: 16097881
A monograph on approaches for logistic optimization of warehouses and related logistic systems.
COBISS.SI-ID: 264707072
We derive some general results on the symmetries of equivelar toroids and provide detailed analysis of the subgroup lattice structure of the dihedral group $D_4$ and of the octahedral group to complete classification by symmetry type of those in ranks 3 and 4.
COBISS.SI-ID: 16478297
The well-known Petersen graph $G(5,2)$ can be drawn in the ordinary Euclidean plane in such a way that each edge is represented as a line segment of length 1. When two vertices are drawn on the same point in the Euclidean plane, drawings are said to be degenerate. In this paper we investigate all such degenerate drawings of the Petersen graph and various relationships among them. A heavily degenerate unit distance planar representation, where the representation of a vertex lies in the interior of the representation of an edge, it does not belong to, is also shown.
COBISS.SI-ID: 16312665