8 citations · 24 across the 25 of their papers we have counts for
5 papers · 1 filter
Novel Adaptive Algorithms for Estimating Betweenness, Coverage and k-path Centralities
Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem
An important index widely used to analyze social and information networks is betweenness centrality. In this paper, first given a directed network and a vertex , we…
Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs
Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem
Graphs (networks) are an important tool to model data in different domains. Real-world graphs are usually directed, where the edges have a direction and they are not symmetric. Bet…
Metropolis-Hastings Algorithms for Estimating Betweenness Centrality in Large Networks
Mostafa Haghir Chehreghani, Talel Abdessalem, and Albert Bifet
Betweenness centrality is an important index widely used in different domains such as social networks, traffic networks and the world wide web. However, even for mid-size networks…
Discriminative Distance-Based Network Indices with Application to Link Prediction
Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem
In large networks, using the length of shortest paths as the distance measure has shortcomings. A well-studied shortcoming is that extending it to disconnected graphs and directed…
Efficient Algorithms for Approximate Triangle Counting
Mostafa Haghir Chehreghani
Counting the number of triangles in a graph has many important applications in network analysis. Several frequently computed metrics like the clustering coefficient and the transit…