activity
20142026
most citedHigher-order motif analysis in hypergraphs

160 citations · 317 across the 15 of their papers we have counts for

collaborators

16 papers

physics.soc-ph2026★ 1 cited

Hypergraphx-data: a repository for higher-order network data

Quintino Francesco Lotito, Lorenzo Betti, Berné Nortier +2

The availability of network datasets advances research in network science, machine learning and related fields by enabling empirical analyses and their reproducibility, algorithm d…

physics.soc-ph2024

The microscale organization of directed hypergraphs

Quintino Francesco Lotito, Alberto Vendramini, Alberto Montresor +1

Many real-world complex systems are characterized by non-pairwise -- higher-order -- interactions among system's units, and can be effectively modeled as hypergraphs. Directed hype…

cs.IR2024

Comparing Personalized Relevance Algorithms for Directed Graphs

Luca Cavalcanti, Cristian Consonni, Martin Brugnara +2

We present an interactive Web platform that, given a directed graph, allows identifying the most relevant nodes related to a given query node. Besides well-established algorithms s…

physics.soc-ph2024★ 15 cited

Multiplex measures for higher-order networks

Quintino Francesco Lotito, Alberto Montresor, Federico Battiston

A wide variety of complex systems are characterized by interactions of different types involving varying numbers of units. Multiplex hypergraphs serve as a tool to describe such st…

physics.soc-ph2023★ 40 cited

Hypergraphx: a library for higher-order network analysis

Quintino Francesco Lotito, Martina Contisciani, Caterina De Bacco +6

From social to biological systems, many real-world systems are characterized by higher-order, non-dyadic interactions. Such systems are conveniently described by hypergraphs, where…

cs.SI2023★ 18 cited

Hyperlink communities in higher-order networks

Quintino Francesco Lotito, Federico Musciotto, Alberto Montresor +1

Many networks can be characterised by the presence of communities, which are groups of units that are closely linked. Identifying these communities can be crucial for understanding…

cs.SI2022★ 23 cited

Exact and sampling methods for mining higher-order motifs in large hypergraphs

Quintino Francesco Lotito, Federico Musciotto, Federico Battiston +1

Network motifs are recurrent, small-scale patterns of interactions observed frequently in a system. They shed light on the interplay between the topology and the dynamics of comple…

physics.soc-ph2021★ 160 cited

Higher-order motif analysis in hypergraphs

Quintino Francesco Lotito, Federico Musciotto, Alberto Montresor +1

A deluge of new data on social, technological and biological networked systems suggests that a large number of interactions among system units are not limited to pairs, but rather…

cs.LG2020

Dynamic Embeddings for Interaction Prediction

Zekarias T. Kefato, Sarunas Girdzijauskas, Nasrullah Sheikh +1

In recommender systems (RSs), predicting the next item that a user interacts with is critical for user retention. While the last decade has seen an explosion of RSs aimed at identi…

cs.CY2020★ 5 cited

A general method for estimating the prevalence of Influenza-Like-Symptoms with Wikipedia data

Giovanni De Toni, Cristian Consonni, Alberto Montresor

Influenza is an acute respiratory seasonal disease that affects millions of people worldwide and causes thousands of deaths in Europe alone. Being able to estimate in a fast and re…

cs.DS2020★ 5 cited

Efficient Algorithms to Mine Maximal Span-Trusses From Temporal Graphs

Quintino Francesco Lotito, Alberto Montresor

Over the last decade, there has been an increasing interest in temporal graphs, pushed by a growing availability of temporally-annotated network data coming from social, biological…

cs.LG2020★ 5 cited

Which way? Direction-Aware Attributed Graph Embedding

Zekarias T. Kefato, Nasrullah Sheikh, Alberto Montresor

Graph embedding algorithms are used to efficiently represent (encode) a graph in a low-dimensional continuous vector space that preserves the most important properties of the graph…

cs.DC2019

Please, do not decentralize the Internet with (permissionless) blockchains!

Pedro Garcia Lopez, Alberto Montresor, Anwitaman Datta

The old mantra of decentralizing the Internet is coming again with fanfare, this time around the blockchain technology hype. We have already seen a technology supposed to change th…

cs.SI2019

WikiLinkGraphs: A Complete, Longitudinal and Multi-Language Dataset of the Wikipedia Link Networks

Cristian Consonni, David Laniado, Alberto Montresor

Wikipedia articles contain multiple links connecting a subject to other pages of the encyclopedia. In Wikipedia parlance, these links are called internal links or wikilinks. We pre…

cs.DC2017★ 24 cited

BLADYG: A Graph Processing Framework for Large Dynamic Graphs

Sabeur Aridhi, Alberto Montresor, Yannis Velegrakis

Recently, distributed processing of large dynamic graphs has become very popular, especially in certain domains such as social network analysis, Web graph analysis and spatial netw…

cs.DC2014★ 21 cited

Distributed Edge Partitioning for Graph Processing

Alessio Guerrieri, Alberto Montresor

The availability of larger and larger graph datasets, growing exponentially over the years, has created several new algorithmic challenges to be addressed. Sequential approaches ha…