8 citations · 15 across the 7 of their papers we have counts for
10 papers
Scalable Katz Ranking Computation in Large Static and Dynamic Graphs
Alexander van der Grinten, Elisabetta Bergamini, Oded Green +2
Network analysis defines a number of centrality measures to identify the most central nodes in a network. Fast computation of those measures is a major challenge in algorithmic net…
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…
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…
Estimating Current-Flow Closeness Centrality with a Multigrid Laplacian Solver
Elisabetta Bergamini, Michael Wegner, Dimitar Lukarski +1
Matrices associated with graphs, such as the Laplacian, lead to numerous interesting graph problems expressed as linear systems. One field where Laplacian linear systems play a rol…
Approximating Betweenness Centrality in Fully-dynamic Networks
Elisabetta Bergamini, Henning Meyerhenke
Betweenness is a well-known centrality measure that ranks the nodes of a network according to their participation in shortest paths. Since an exact computation is prohibitive in la…
Fully-dynamic Approximation of Betweenness Centrality
Elisabetta Bergamini, Henning Meyerhenke
Betweenness is a well-known centrality measure that ranks the nodes of a network according to their participation in shortest paths. Since an exact computation is prohibitive in la…
Approximating Betweenness Centrality in Large Evolving Networks
Elisabetta Bergamini, Henning Meyerhenke, Christian L. Staudt
Betweenness centrality ranks the importance of nodes by their participation in all shortest paths of the network. Therefore computing exact betweenness values is impractical in lar…