Ariadne Lab

Network Robustness and Resilience

Mon, 01 Jan 0001 00:00:00 +0000

Research focus

Failures and targeted interventions can change the connectivity and function of a complex system. We study theoretical and computational methods for describing that response, with particular attention to network dismantling: identifying a small set of nodes or edges whose removal fragments a network.

This work includes comparisons of dismantling methods, machine-learning approaches to structural intervention and indicators that anticipate network disintegration.

Selected publications

Robustness and resilience of complex networks, Nature Reviews Physics (2024)
Machine learning dismantling and early-warning signals of disintegration in complex systems, Nature Communications (2021)
Latent Geometry-Driven Network Automata for Complex Network Dismantling, ICLR (2026)

Code and data

The network dismantling review resource collects implementations, benchmark networks and reproducibility material associated with the 2024 review.

Multilayer Networks and Mesoscale Structure

Mon, 01 Jan 0001 00:00:00 +0000

Research focus

Many systems contain several kinds of interaction and organise themselves at scales between individual nodes and the network as a whole. Multilayer models keep different relations distinct; community-detection and flow-based methods help reveal the resulting mesoscale organisation.

Our work has examined the community structure of multilayer systems, molecular networks, international trade and global value chains. The common question is which structural information is lost when heterogeneous relations are reduced to a single graph.

Molecular networks and biological function

Our study of the human proteome, with Giuseppe Jurman and Manlio De Domenico, keeps molecular interaction layers separate when identifying functional modules with Multiplex Infomap. Its random walker follows the links of its current layer and, with a probability called the relax rate, the links of any layer, which lets it move between layers. An information-theoretic criterion selects this rate.

Comparing the resulting modules with independently annotated gene sets assesses their biological relevance. The selected multilayer organisation has greater functional content than modules obtained from the aggregate representation, connecting a modelling choice to an external biological assessment.

Selected publications

The nested structural organization of the worldwide trade multi-layer network, Scientific Reports (2019)
Modularity in multilayer networks using redundancy-based resolution and projection-based inter-layer coupling, IEEE Transactions on Network Science and Engineering (2019)
Multilayer flows in molecular networks identify biological modules in the human proteome, IEEE Transactions on Network Science and Engineering (2020)

Learning on Graphs

Mon, 01 Jan 0001 00:00:00 +0000

Research focus

Graph data are rarely homogeneous. Relations may be weighted, signed, organised in layers or observed only indirectly. We study learning methods that preserve and exploit this structure rather than flattening it before analysis.

This line includes graph neural networks for non-standard graph structures, link prediction, graph generation and methods for evaluating or interpreting learned network representations. Besides predictive performance, we look for models whose assumptions and outputs can be related back to network structure.

Selected publications

wsGAT: Weighted and Signed Graph Attention Networks for Link Prediction, Complex Networks (2021)
mGNN: Generalizing the Graph Neural Networks to the Multilayer Case, arXiv preprint (2021)
Beyond MMD: Evaluating Graph Generative Models with Geometric Deep Learning, arXiv preprint (2025)
ProtoGuide: Prototype-Driven Guidance for Class-Conditional Graph Generation, arXiv preprint (2026)

Graph Algorithms and Combinatorial Optimisation

Mon, 01 Jan 0001 00:00:00 +0000

Research focus

Many questions about complex networks lead to computationally difficult graph problems. We investigate hybrid approaches in which a solver stays in charge and learning helps it decide where to search, which elements to prune or which intervention to evaluate next.

Our papers cover search-space reduction for maximum-clique problems and node- or edge-based network dismantling. Across these settings, we are interested in scalability, comparison against strong algorithmic baselines and what the learned strategy reveals about the structure of the problem.

Selected publications

Learning fine-grained search space pruning and heuristics for combinatorial optimization, Journal of Heuristics (2023)
Geometric deep learning sub-network extraction for maximum clique enumeration, PLOS ONE (2024)
Edge Dismantling with Geometric Reinforcement Learning, Complex Networks (2024)

Mediterranean School of Complex Networks

Sat, 17 Oct 2026 00:00:00 +0000

The school brings lecturers and PhD students together for a week of lectures, invited talks and participants’ flash talks on the theory and applications of complex networks. In 2022 it merged with ISI&DCN, the school the lab organised at the University of Catania in 2018 and 2020, whose organisers joined the MSCX directors.

The first six editions, from 2014 to 2019, were held on Salina and directed by Alex Arenas and Manlio De Domenico. There is no 2026 edition: the school is taking a year to rework its programme and returns in 2027.

Food Connections: Data and Simulation Tools

Fri, 09 Oct 2026 00:00:00 +0000

About the resource

Food Connections studies how international trade and the rules governing it relate to food and nutrition security and environmental sustainability. The project portal brings together materials and results, with entry points to data, simulation code and an early-warning application.

Use the resource

Visit the Food Connections portal

Consult the linked resources for documentation, data provenance and citation requirements.

What a generated graph should preserve

Mon, 14 Sep 2026 00:00:00 +0000

Generating graphs with plausible summary statistics does not guarantee that they retain the structural characteristics of a real network domain. Our work examines both how to evaluate this correspondence and how to guide generation towards a specified class of networks.

Beyond MMD introduces representation-aware evaluation using geometric deep learning. Its comparison of graph generators shows that agreement on selected topological statistics can coexist with a loss of the structural features that distinguish graph domains.

ProtoGuide uses a learned graph representation and target-class prototypes to guide a frozen discrete graph generator. The guidance can be retargeted by changing the prototype without retraining the generator. Experiments with two generative backbones show improved target-class fidelity, with effects on coverage and diversity that vary across classes and settings.

Both selected papers are preprints. Together they address a common question: what should a generated network preserve beyond a small set of summary statistics?

A digital twin should make a risky claim

Fri, 11 Sep 2026 00:00:00 +0000

Graph-Based Analysis of Attentional Fidelity in Brain-To-Image Reconstruction

Tue, 01 Sep 2026 00:00:00 +0000

Unveiling core-collapse supernova progenitors: characterization and physical insights through explainable artificial intelligence

Mon, 06 Jul 2026 00:00:00 +0000

Brain-Grasp: Graph-Based Saliency Priors for Improved FMRI-Based Visual Brain Decoding

Sun, 03 May 2026 00:00:00 +0000

From brain signals to meaningful networks

Thu, 09 Apr 2026 00:00:00 +0000

How can we reconstruct informative networks when we observe the activity of individual brain regions? Our work examines which collective patterns of co-activation carry useful information about subjects and conditions.

Functional brain networks reconstructed from fMRI usually rely on statistical pruning: each correlation between two regions of interest is thresholded independently, ignoring collective co-activation patterns within sub-networks. Functional pruning instead retains connections for their collective importance in distinguishing healthy from affected individuals.

We build multilayer network representations from a multi-frequency decomposition of the signals, learn them with geometric deep learning, and use an explainable-AI tool to identify the most discriminative sub-networks.

Machine-enhanced reconstruction of functional connectomes unravels discriminative brain sub-systems in health and disease

Thu, 09 Apr 2026 00:00:00 +0000

LLMsFold: Integrating Large Language Models and Biophysical Simulations for De Novo Drug Design

Wed, 04 Mar 2026 00:00:00 +0000

Contact

Fri, 27 Feb 2026 00:00:00 +0000

Looking for a thesis? Start from Thesis projects, with the open areas and the steps to follow. The other researchers’ contacts are on the People page.

Influence of the reinsertion algorithm on the performance of the Vertex Entanglement method

Wed, 07 Jan 2026 00:00:00 +0000

ProtoGuide: Prototype-Driven Guidance for Class-Conditional Graph Generation

Thu, 01 Jan 2026 00:00:00 +0000

Graph-Based Evaluation of Visual Brain Decoding from fMRI Data

Mon, 08 Dec 2025 00:00:00 +0000

Latent Geometry-Driven Network Automata for Complex Network Dismantling

Mon, 08 Dec 2025 00:00:00 +0000

Understanding network robustness

Mon, 08 Dec 2025 00:00:00 +0000

Local failures can propagate through a network, changing its structure and function. Understanding robustness and resilience means asking how much disruption a system can withstand, how it responds and which interventions can reduce the impact.

Our review in Nature Reviews Physics (2024) brings together theoretical and computational approaches to these questions, including the design of robust networks, early-warning signals and adaptive responses. It also compares dismantling techniques and provides ready-to-use scripts.

Network dismantling probes structural vulnerability by finding a small set of units whose removal fragments a network. Finding a minimum set is computationally challenging (NP-hard), so practical approaches often rely on heuristics.

A machine trained to dismantle relatively small systems identifies higher-order topological patterns and disintegrates large-scale social, infrastructural and technological networks more efficiently than human-based heuristics. It also assesses the probability that the next attacks will disintegrate the system, a quantitative early-warning signal of collapse (Nature Communications, 2021).

Latent Geometry-Driven Network Automata use local rules to approximate effective link distances and outperform existing dismantling algorithms, validated on 1,475 real-world networks across 32 domains (ICLR 2026).

How Well is Human Attention Preserved in fMRI-Based VisualBrain Decoding?

Mon, 06 Oct 2025 00:00:00 +0000

What is Wrong with Visual Brain Decoding? A Saliency-based Investigation

Mon, 30 Jun 2025 00:00:00 +0000

Machine Learning Supernovae’s Progenitor Characterization

Wed, 12 Mar 2025 00:00:00 +0000

Beyond MMD: Evaluating Graph Generative Models with Geometric Deep Learning

Wed, 01 Jan 2025 00:00:00 +0000

Saliency Matters: From Nodes to Objects

Wed, 01 Jan 2025 00:00:00 +0000

Geometric Deep Learning sub-network extraction for Maximum Clique Enumeration

Tue, 16 Jan 2024 00:00:00 +0000

Network Dismantling Review: Code and Data

Mon, 08 Jan 2024 00:00:00 +0000

About the resource

This repository accompanies the review:

O. Artime, M. Grassia, M. De Domenico, J. P. Gleeson, H. A. Makse, G. Mangioni, M. Perc, and F. Radicchi. Robustness and resilience of complex networks. Nature Reviews Physics 6, 114–131 (2024).

It brings together implementations and wrappers for network dismantling methods, benchmark networks used in the review and scripts for reproducing comparative results. Network dismantling studies how removing selected nodes or edges changes the connectivity of a network.

Use the resource

Installation and execution instructions are maintained in the repository so that they remain aligned with the code.

Citation and licence

Please cite the review and the original publications for any individual algorithm used. Code produced for the review is released under GPLv3; individual algorithm wrappers can retain the licences of their original implementations. Consult the repository before redistribution or reuse.

Robustness and resilience of complex networks

Mon, 08 Jan 2024 00:00:00 +0000

Edge Dismantling with Geometric Reinforcement Learning

Mon, 01 Jan 2024 00:00:00 +0000

Regionalisation and cross-region integration. Twin dynamics in the automotive international trade networks

Fri, 01 Dec 2023 00:00:00 +0000

The layered structure of global trade

Fri, 01 Dec 2023 00:00:00 +0000

International trade connects countries through different commodities and industries. Keeping those relations separate reveals structures that an aggregate trade network can obscure, from commodity-specific communities to interactions within and across production sectors.

Our studies examine the multilayer organisation of global value chains, communities in food trade, and regionalisation and cross-region integration in automotive trade. These perspectives describe how trading relationships are organised at several scales.

Network-based simulations also examine how shocks to domestic food production propagate through international trade. They show that exposure to external shocks and protection against domestic shortages differ across countries. The structure of trade therefore matters when assessing food-security risks.

The Food Connections resource page links to project materials, data and simulation tools on trade and food and nutrition security.

Efficient Node PageRank Improvement via Link-building using Geometric Deep Learning

Fri, 30 Jun 2023 00:00:00 +0000

Learning fine-grained search space pruning and heuristics for combinatorial optimization

Thu, 01 Jun 2023 00:00:00 +0000

Complex Networks XIII: Proceedings of the 13th Conference on Complex Networks, CompleNet 2022

Sun, 01 Jan 2023 00:00:00 +0000

Complex Networks XIV: Proceedings of the 14th Conference on Complex Networks, CompleNet 2023

Sun, 01 Jan 2023 00:00:00 +0000

CoreGDM: Geometric Deep Learning Network Decycling and Dismantling

Sun, 01 Jan 2023 00:00:00 +0000

CoreGDM: Network Decycling and Dismantling

Sun, 01 Jan 2023 00:00:00 +0000

About the resource

CoreGDM was introduced in:

M. Grassia and G. Mangioni. CoreGDM: Geometric Deep Learning Network Decycling and Dismantling. Complex Networks XIV (2023).

It merges the GDM framework with the CoreHD algorithm: it attacks the 2-core of the network, using a learned score in place of the node degree.

Use the resource

The CoreGDM repository points to the review package for now; the stand-alone code is not published yet.

Citation and licence

Please cite the paper. The code is released under GPLv3.

Correlation Between Researchers’ Centrality and H-Index: A Case Study

Sun, 01 Jan 2023 00:00:00 +0000

Geometric Deep Learning Graph Pruning to Speed-Up the Run-Time of Maximum Clique Enumerarion Algorithms

Sun, 01 Jan 2023 00:00:00 +0000

Editorial: Scalable Network Generation & Analysis

Mon, 25 Jul 2022 00:00:00 +0000

Co-Authorship Networks Analysis to Discover Collaboration Patterns among Italian Researchers

Thu, 16 Jun 2022 00:00:00 +0000

The rise and fall of countries in the global value chains

Tue, 31 May 2022 00:00:00 +0000

Insights into countries’ exposure and vulnerability to food trade shocks from network-based simulations

Thu, 17 Mar 2022 00:00:00 +0000

Link Prediction in Time Varying Social Networks

Tue, 01 Mar 2022 00:00:00 +0000

Analysis of the Co-authorship Sub-networks of Italian Academic Researchers

Sat, 01 Jan 2022 00:00:00 +0000

Automotive Value Chains in a Brave New World

Sat, 01 Jan 2022 00:00:00 +0000

Network Topology to Predict Bibliometrics Indices: A Case Study

Sat, 01 Jan 2022 00:00:00 +0000

Preliminary Characterization of Italian Academic Scholars by Their Bibliometrics

Sat, 01 Jan 2022 00:00:00 +0000

Relations Between Entropy and Accuracy Trends in Complex Artificial Neural Networks

Sat, 01 Jan 2022 00:00:00 +0000

The Changing Shape of the World Automobile Industry: A Multilayer Network Analysis of International Trade in Components and Parts

Sat, 01 Jan 2022 00:00:00 +0000

wsGAT: Weighted and Signed Graph Attention

Sat, 01 Jan 2022 00:00:00 +0000

About the resource

This repository accompanies the paper:

M. Grassia and G. Mangioni. wsGAT: Weighted and Signed Graph Attention Networks for Link Prediction. Complex Networks & Their Applications X (2022).

wsGAT extends the Graph Attention Network (GAT) layer to graphs whose links carry a weight and a sign, such as trust and correlation networks. The paper uses it to predict the weight, the sign and the existence of links.

Use the resource

The repository contains the layer, wsGATConv, written for PyTorch Geometric.

Citation and licence

Please cite the paper. The code is released under GPLv3.

wsGAT: Weighted and Signed Graph Attention Networks for Link Prediction

Sat, 01 Jan 2022 00:00:00 +0000

(Unintended) Consequences of export restrictions on medical goods during the Covid-19 pandemic

Mon, 20 Dec 2021 00:00:00 +0000

GDM: Graph Dismantling with Machine Learning

Tue, 31 Aug 2021 00:00:00 +0000

About the resource

This repository accompanies the paper:

M. Grassia, M. De Domenico, and G. Mangioni. Machine learning dismantling and early-warning signals of disintegration in complex systems. Nature Communications 12, 5190 (2021).

A graph neural network trained to dismantle small synthetic networks is used to attack large real-world ones, and its predictions give an early-warning signal of the network’s collapse. The repository holds the scripts, the networks used for training and testing, and the pre-trained models.

Use the resource

Setup and reproduction instructions are in the repository. Only part of the real-world test networks is included, because the original data come under different licences.

Citation and licence

Please cite the paper, and the archived release when you use the code. The code is released under GPLv3.

Machine learning dismantling and early-warning signals of disintegration in complex systems

Tue, 31 Aug 2021 00:00:00 +0000

Mutual Influence of Users Credibility and News Spreading in Online Social Networks

Sun, 25 Apr 2021 00:00:00 +0000

A Network-Based Analysis of a Worksite Canteen Dataset

Mon, 08 Mar 2021 00:00:00 +0000

Food Recommendation in a Worksite Canteen

Fri, 01 Jan 2021 00:00:00 +0000

mGNN: Generalizing the Graph Neural Networks to the Multilayer Case

Fri, 01 Jan 2021 00:00:00 +0000

Wind Farms Maintenance Optimization Using a Pickup and Delivery VRP Algorithm

Fri, 01 Jan 2021 00:00:00 +0000

A network-based analysis to understand food-habits of a multi-company canteen's customers

Mon, 30 Nov 2020 00:00:00 +0000

Pick-up & Deliver in Maintenance Management of Renewable Energy Power Plants

Sat, 26 Sep 2020 00:00:00 +0000

Modularity in Multilayer Networks Using Redundancy-Based Resolution and Projection-Based Inter-Layer Coupling

Wed, 01 Jul 2020 00:00:00 +0000

Complex Networks XI: Proceedings of the 11th Conference on Complex Networks CompleNet 2020

Wed, 01 Jan 2020 00:00:00 +0000

Credibility-based Model for News Spreading on Online Social Networks

Wed, 01 Jan 2020 00:00:00 +0000

Group Cohesion Assessment in Networks

Wed, 01 Jan 2020 00:00:00 +0000

Multilayer Flows in Molecular Networks Identify Biological Modules in the Human Proteome

Wed, 01 Jan 2020 00:00:00 +0000

Preface

Wed, 01 Jan 2020 00:00:00 +0000

Smart Topic Sharing in IoT Platform Based on a Social Inspired Broker

Wed, 01 Jan 2020 00:00:00 +0000

Strategies Comparison in Link Building Problem

Wed, 01 Jan 2020 00:00:00 +0000

Network robustness improvement via long-range links

Sun, 01 Dec 2019 00:00:00 +0000

The nested structural organization of the worldwide trade multi-layer network

Wed, 27 Feb 2019 00:00:00 +0000

A PageRank Inspired Approach to Measure Network Cohesiveness

Tue, 01 Jan 2019 00:00:00 +0000

A Social Inspired Broker for M2M Protocols

Tue, 01 Jan 2019 00:00:00 +0000

Learning Multi-Stage Sparsification for Maximum Clique Enumeration

Tue, 01 Jan 2019 00:00:00 +0000

Long distance connections for ranking and robustness enhancement in networks

Tue, 01 Jan 2019 00:00:00 +0000

Managing Privacy in a Social Broker Internet of Thing

Tue, 01 Jan 2019 00:00:00 +0000

Unfolding the Complexity of the Global Value Chain: Strength and Entropy in the Single-Layer, Multiplex, and Multi-Layer International Trade Networks

Wed, 28 Nov 2018 00:00:00 +0000

Identifying the community structure of the food-trade international multi-network

Thu, 10 May 2018 00:00:00 +0000

Black hole metric: Overcoming the pagerank normalization problem

Sun, 01 Apr 2018 00:00:00 +0000

A Trust-Based News Spreading Model

Mon, 01 Jan 2018 00:00:00 +0000

Climbing Ranking Position via Long-Distance Backlinks

Mon, 01 Jan 2018 00:00:00 +0000

Exploiting Long Distance Connections to Strengthen Network Robustness

Mon, 01 Jan 2018 00:00:00 +0000

Introducing Credibility to Model News Spreading

Mon, 01 Jan 2018 00:00:00 +0000

Long Distance In-Links for Ranking Enhancement

Mon, 01 Jan 2018 00:00:00 +0000

Post Sharing-Based Credibility Network for Social Network

Mon, 01 Jan 2018 00:00:00 +0000

Terrorism and War: Twitter Cascade Analysis

Mon, 01 Jan 2018 00:00:00 +0000

Direct trust assignment using social reputation and aging

Sat, 01 Apr 2017 00:00:00 +0000

Dealing with the Best Attachment Problem via Heuristics

Sun, 01 Jan 2017 00:00:00 +0000

Evaluating the community partition quality of a network with a genetic programming approach

Sun, 01 Jan 2017 00:00:00 +0000

Network size and topology impact on trust-based ranking

Sun, 01 Jan 2017 00:00:00 +0000

Social-Based Arcs Weight Assignment in Trust Networks

Fri, 01 Jan 2016 00:00:00 +0000

Tourism Websites Network: Crawling the Italian Webspace

Fri, 01 Jan 2016 00:00:00 +0000

Multisource agent-based healthcare data gathering

Sun, 11 Oct 2015 00:00:00 +0000

Searching for experts in a context-aware recommendation network

Thu, 01 Oct 2015 00:00:00 +0000

Complex Networks VI: Proceedings of the 6th Workshop on Complex Networks CompleNet 2015

Thu, 01 Jan 2015 00:00:00 +0000

CORSA: An Open Solution for Social Oriented Real-time Ride Sharing

Thu, 01 Jan 2015 00:00:00 +0000

In Complex Networks VI

Thu, 01 Jan 2015 00:00:00 +0000

The cost of trust in the dynamics of best attachment

Thu, 01 Jan 2015 00:00:00 +0000

The Effect of Topology on the Attachment Process in Trust Networks

Thu, 01 Jan 2015 00:00:00 +0000

Social system as complex networks

Mon, 01 Dec 2014 00:00:00 +0000

An Intelligent and Pervasive Surveillance System for Home Security

Sat, 20 Sep 2014 00:00:00 +0000

Virtualization for Effective Risk-Free Network Security Assessment

Sat, 13 Sep 2014 00:00:00 +0000

A Carpooling Open Application with Social Oriented Reward Mechanism

Wed, 01 Jan 2014 00:00:00 +0000

A Heuristic to Explore Trust Networks Dynamics

Wed, 01 Jan 2014 00:00:00 +0000

Connecting relatives in virtual worlds: The kinship networks

Sun, 01 Sep 2013 00:00:00 +0000

A Growing Model for Scale–Free Networks Embedded in Hyperbolic Metric Spaces

Tue, 01 Jan 2013 00:00:00 +0000

Complex Networks IV

Tue, 01 Jan 2013 00:00:00 +0000

Crafting Kinship Networks by Exploring Acquaintances Relationships

Tue, 01 Jan 2013 00:00:00 +0000

The Effects of Pre-trusted Peers Misbehaviour on EigenTrust

Tue, 01 Jan 2013 00:00:00 +0000

The Relevance of Context in Trust Networks

Tue, 01 Jan 2013 00:00:00 +0000

Users' attachment in trust networks: reputation vs. effort

Tue, 01 Jan 2013 00:00:00 +0000

Trust assessment: a personalized, distributed, and secure approach

Wed, 25 Apr 2012 00:00:00 +0000

Trust into e-Learning

Sun, 01 Jan 2012 00:00:00 +0000

Identifying the community structure of the international-trade multi-network

Wed, 01 Jun 2011 00:00:00 +0000

Communications in Computer and Information Science:Preface

Sat, 01 Jan 2011 00:00:00 +0000

Communities Unfolding in Multislice Networks

Sat, 01 Jan 2011 00:00:00 +0000

Community Structure in the Multi-network of International Trade

Sat, 01 Jan 2011 00:00:00 +0000

Complex Networks: Second International Workshop, CompleNet 2010, Rio de Janeiro, Brazil, October 13-15, 2010, Revised Selected Papers

Sat, 01 Jan 2011 00:00:00 +0000

Gain the Best Reputation in Trust Networks

Sat, 01 Jan 2011 00:00:00 +0000

Intelligent distributed information systems

Sat, 01 May 2010 00:00:00 +0000

An adaptive overlay network inspired by social behaviour

Mon, 01 Mar 2010 00:00:00 +0000

A Distributed Algorithm for Personalized Trust Evaluation in Social Networks

Fri, 01 Jan 2010 00:00:00 +0000

Context-based global expertise in recommendation systems

Fri, 01 Jan 2010 00:00:00 +0000

Pervasive Home Security: An Intelligent Domotics Application

Fri, 01 Jan 2010 00:00:00 +0000

Effective Classification of Enterprise Reports in Production Assessment

Tue, 01 Dec 2009 00:00:00 +0000

Struggling with misbehaviours in trust systems

Tue, 01 Dec 2009 00:00:00 +0000

The effect of malicious peers in a gossip-based reputation system

Tue, 24 Nov 2009 00:00:00 +0000

Advertising and Discovering Trusted Resources within a P2P-Based Architecture

Wed, 01 Jul 2009 00:00:00 +0000

Resource advertising in PROSA P2P network

Fri, 01 May 2009 00:00:00 +0000

Extending the definition of modularity to directed graphs with overlapping communities

Mon, 16 Mar 2009 00:00:00 +0000

Complex Networks: Results of the 2009 International Workshop on Complex Networks (CompleNet 2009)

Thu, 01 Jan 2009 00:00:00 +0000

Discovering Community Structure on Large Networks Using a Grid Computing Environment

Thu, 01 Jan 2009 00:00:00 +0000

Exploiting trust into e-learning: adding reliability to learning paths

Thu, 01 Jan 2009 00:00:00 +0000

Search for overlapped communities by parallel genetic algorithms

Thu, 01 Jan 2009 00:00:00 +0000

The Assessment of Expertise in Social Networks

Thu, 01 Jan 2009 00:00:00 +0000

Emerging structures of P2P networks induced by social relationships

Fri, 01 Feb 2008 00:00:00 +0000

Adaptive E–Learning: An Architecture Based on PROSA P2P Network

Tue, 01 Jan 2008 00:00:00 +0000

Applying Social Behaviours to Model Trusting

Tue, 01 Jan 2008 00:00:00 +0000

Intelligent Distributed Computing, Systems and Applications: Proceedings of the 2nd International Symposium on Intelligent Distributed Computing: IDC 2008, Catania, Italy, 18-19.09. 2008

Tue, 01 Jan 2008 00:00:00 +0000

PROSA: P2P Resource Organisation by Social Acquaintances

Tue, 01 Jan 2008 00:00:00 +0000

Reliable Personalized Learning Paths: The Contribution of Trust to E-Learning

Tue, 01 Jan 2008 00:00:00 +0000

The dilemma of trust: A social network based approach

Tue, 01 Jan 2008 00:00:00 +0000

Trusting Evaluation by Social Reputation

Tue, 01 Jan 2008 00:00:00 +0000

On robustness and self-adaptiveness of a socially inspired P2P network

Thu, 01 Nov 2007 00:00:00 +0000

A model for a web-based learning system

Sun, 01 Jul 2007 00:00:00 +0000

Fast Information Retrieval in a Self–Organising P2P Network

Sun, 01 Jul 2007 00:00:00 +0000

An Approach to Trust Based on Social Networks

Mon, 01 Jan 2007 00:00:00 +0000

An architecture to support adaptive e-learning

Mon, 01 Jan 2007 00:00:00 +0000

Efficient Searching and Retrieval of Documents in PROSA

Mon, 01 Jan 2007 00:00:00 +0000

Evaluating the Dynamic Behaviour of PROSA P2P Network

Sun, 01 Jan 2006 00:00:00 +0000

Exploiting Social Networks Dynamics for P2P Resource Organisation

Sun, 01 Jan 2006 00:00:00 +0000

Self-Organisation of Resources in PROSA P2P Network

Sun, 01 Jan 2006 00:00:00 +0000

Social Behaviours in P2P Systems: An Efficient Algorithm for Resource Organisation

Sun, 01 Jan 2006 00:00:00 +0000

Using web-based personalized learning system in academic context

Thu, 01 Jan 2004 00:00:00 +0000

A Tool for Performance Evaluation in a Formal Codesign Framework

Mon, 01 Sep 2003 00:00:00 +0000

TTL: a modular language for hardware/software systems design

Sat, 01 Mar 2003 00:00:00 +0000

Automatic generation of learning paths

Wed, 01 Jan 2003 00:00:00 +0000

Courses Modeling in E-learning Context

Wed, 01 Jan 2003 00:00:00 +0000

Courses personalization in an e-learning environment

Wed, 01 Jan 2003 00:00:00 +0000

From Specification to Hardware Device: A Synthesis Algorithm

Wed, 01 Jan 2003 00:00:00 +0000

Synthesis of LOTOS specification of the IEEE-1394 firewire protocol

Wed, 01 Jan 2003 00:00:00 +0000

ESA: an approach to Systems Design by Equation Solving

Mon, 01 Jan 2001 00:00:00 +0000

Using a Formal Framework for Agent System Design

Mon, 01 Jan 2001 00:00:00 +0000

Hardware/software synthesis of formal specifications in codesign of embedded systems

Sat, 01 Jul 2000 00:00:00 +0000

A Method to Implement Information Systems by Reusable Components