187 citations · 581 across the 39 of their papers we have counts for
6 papers · 2 filters
Computing Top-k Closeness Centrality in Fully-dynamic Graphs
Patrick Bisenius, Elisabetta Bergamini, Eugenio Angriman +1
Closeness is a widely-studied centrality measure. Since it requires all pairwise distances, computing closeness for all nodes is infeasible for large real-world networks. However,…
Scaling up Group Closeness Maximization
Elisabetta Bergamini, Tanya Gonser, Henning Meyerhenke
Closeness is a widely-used centrality measure in social network analysis. For a node it indicates the reciprocal of the average shortest-path distance to the other nodes of the net…
Maxent-Stress Optimization of 3D Biomolecular Models
Michael Wegner, Oskar Taubert, Alexander Schug +1
Knowing a biomolecule's structure is inherently linked to and a prerequisite for any detailed understanding of its function. Significant effort has gone into developing technologie…
Faster Betweenness Centrality Updates in Evolving Networks
Elisabetta Bergamini, Henning Meyerhenke, Mark Ortmann +1
Finding central nodes is a fundamental problem in network analysis. Betweenness centrality is a well-known measure which quantifies the importance of a node based on the fraction o…
Computing top-k Closeness Centrality Faster in Unweighted Graphs
Elisabetta Bergamini, Michele Borassi, Pierluigi Crescenzi +2
Given a connected graph , the closeness centrality of a vertex is defined as . This measure is widely used in the analysis of real-w…
Improving the betweenness centrality of a node by adding links
Elisabetta Bergamini, Pierluigi Crescenzi, Gianlorenzo D'Angelo +3
Betweenness is a well-known centrality measure that ranks the nodes according to their participation in the shortest paths of a network. In several scenarios, having a high between…