485 citations · 1.2k across the 47 of their papers we have counts for
15 papers · 1 filter
Hyper-distance Oracles in Hypergraphs
Giulia Preti, Gianmarco De Francisci Morales, Francesco Bonchi
We study point-to-point distance estimation in hypergraphs, where the query is parameterized by a positive integer s, which defines the required level of overlap for two hyperedges…
Balancing Utility and Fairness in Submodular Maximization (Technical Report)
Yanhao Wang, Yuchen Li, Francesco Bonchi +1
Submodular function maximization is a fundamental combinatorial optimization problem with plenty of applications -- including data summarization, influence maximization, and recomm…
FreSCo: Mining Frequent Patterns in Simplicial Complexes
Giulia Preti, Gianmarco De Francisci Morales, Francesco Bonchi
Simplicial complexes are a generalization of graphs that model higher-order relations. In this paper, we introduce simplicial patterns -- that we call simplets -- and generalize th…
Multi-relation Graph Summarization
Xiangyu Ke, Arijit Khan, Francesco Bonchi
Graph summarization is beneficial in a wide range of applications, such as visualization, interactive and exploratory analysis, approximate query processing, reducing the on-disk s…
Better Fewer but Better: Community Search with Outliers
Francesco Bonchi, Lorenzo Severini, Mauro Sozio
Given a set of vertices in a network, that we believe are of interest for the application under analysis, community search is the problem of producing a subgraph potentially explai…
Adaptive Community Search in Dynamic Networks
Ioanna Tsalouchidou, Francesco Bonchi, Ricardo Baeza-Yates
Community search is a well-studied problem which, given a static graph and a query set of vertices, requires to find a cohesive (or dense) subgraph containing the query vertices. I…
Finding Densest -Connected Subgraphs
Francesco Bonchi, David García-Soriano, Atsushi Miyauchi +1
Dense subgraph discovery is an important graph-mining primitive with a variety of real-world applications. One of the most well-studied optimization problems for dense subgraph dis…
Query-Efficient Correlation Clustering
David García-Soriano, Konstantin Kutzkov, Francesco Bonchi +1
Correlation clustering is arguably the most natural formulation of clustering. Given n objects and a pairwise similarity measure, the goal is to cluster the objects so that, to the…
Span-core Decomposition for Temporal Networks: Algorithms and Applications
Edoardo Galimberti, Martino Ciaperoni, Alain Barrat +3
When analyzing temporal networks, a fundamental task is the identification of dense structures (i.e., groups of vertices that exhibit a large number of links), together with their…
Distance-generalized Core Decomposition
Francesco Bonchi, Arijit Khan, Lorenzo Severini
The -core of a graph is defined as the maximal subgraph in which every vertex is connected to at least other vertices within that subgraph. In this work we introduce a dista…
Core Decomposition in Multilayer Networks: Theory, Algorithms, and Applications
Edoardo Galimberti, Francesco Bonchi, Francesco Gullo +1
Multilayer networks are a powerful paradigm to model complex systems, where multiple relations occur between the same entities. Despite the keen interest in a variety of tasks, alg…
Fair-by-design matching
David García-Soriano, Francesco Bonchi
Matching algorithms are used routinely to match donors to recipients for solid organs transplantation, for the assignment of medical residents to hospitals, record linkage in datab…
Uncertain Graph Sparsification
Panos Parchas, Nikolaos Papailiou, Dimitris Papadias +1
Uncertain graphs are prevalent in several applications including communications systems, biological databases and social networks. The ever increasing size of the underlying data r…
Scalable Online Betweenness Centrality in Evolving Graphs
Nicolas Kourtellis, Gianmarco De Francisci Morales, Francesco Bonchi
Betweenness centrality is a classic measure that quantifies the importance of a graph element (vertex or edge) according to the fraction of shortest paths passing through it. This…
Local correlation clustering
Francesco Bonchi, David García-Soriano, Konstantin Kutzkov
Correlation clustering is perhaps the most natural formulation of clustering. Given objects and a pairwise similarity measure, the goal is to cluster the objects so that, to th…