Search results for "Complex networks"

showing 10 items of 49 documents

Graph Comparison and Artificial Models for Simulating Real Criminal Networks

2021

Network Science is an active research field, with numerous applications in areas like computer science, economics, or sociology. Criminal networks, in particular, possess specific topologies which allow them to exhibit strong resilience to disruption. Starting from a dataset related to meetings between members of a Mafia organization which operated in Sicily during 2000s, we here aim to create artificial models with similar properties. To this end, we use specific tools of Social Network Analysis, including network models (Barabási-Albert identified to be the most promising) and metrics which allow us to quantify the similarity between two networks. To the best of our knowledge, the DeltaCo…

Settore INF/01 - Informaticabusiness.industryComplex networksContext (language use)Network scienceGraph theoryComplex networkGraph comparisonMachine learningcomputer.software_genreNetwork topologyCriminal networksGraph similarityGraph theorySocial network analysisGraph (abstract data type)Graph matchingArtificial intelligencebusinessResilience (network)Social network analysiscomputer
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Studying micro-communities in Facebook Communities

2018

In the visionary view of the future Internet, named the Next Generation Internet, a current idea is to have a user-centric approach where human behavior models will be used to define the networks or to manage services. During the last years, a great trend in current Social Media platforms is to offer the opportunity to establish and join groups of people online. Despite human behaviour in current Online Social Media have been studied in depth, characteristics of these aggregations of people in content-based communities are still unknown. In this paper, we propose an evaluation of micro-communities of users inside the big network of Facebook groups to understand how and when users are active…

Social Networks AnalysiSettore INF/01 - Informaticabusiness.industryInternet privacyComplex NetworkCommunity Detection; Complex Networks; Facebook Groups Analysis; Social Networks Analysis020206 networking & telecommunications02 engineering and technologyComplex networkComplex NetworksHuman-Computer InteractionSocial groupComputer Networks and CommunicationFacebook Groups AnalysiFacebook Groups Analysis0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingThe InternetSocial mediaSociologySocial Networks AnalysisbusinessCommunity DetectionSoftware1707Proceedings of the 4th EAI International Conference on Smart Objects and Technologies for Social Good
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High-frequency trading and networked markets

2021

Financial markets have undergone a deep reorganization during the last 20 y. A mixture of technological innovation and regulatory constraints has promoted the diffusion of market fragmentation and high-frequency trading. The new stock market has changed the traditional ecology of market participants and market professionals, and financial markets have evolved into complex sociotechnical institutions characterized by a great heterogeneity in the time scales of market members’ interactions that cover more than eight orders of magnitude. We analyze three different datasets for two highly studied market venues recorded in 2004 to 2006, 2010 to 2011, and 2018. Using methods of complex network th…

Statistically validated networks050208 financeMultidisciplinarySociotechnical systemFinancial markets05 social sciencesFinancial marketEvolutionary Models of Financial Markets Special FeatureComplex networksMonetary economicsComplex networkSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Market liquidity0502 economics and businessPortfolioStock marketBusiness050207 economicsHigh-frequency tradingHigh-frequency tradingStock (geology)Proceedings of the National Academy of Sciences
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Correlation Analysis of Node and Edge Centrality Measures in Artificial Complex Networks

2021

The role of an actor in a social network is identified through a set of measures called centrality. Degree centrality, betweenness centrality, closeness centrality, and clustering coefficient are the most frequently used metrics to compute the node centrality. Their computational complexity in some cases makes unfeasible, when not practically impossible, their computations. For this reason, we focused on two alternative measures, WERW-Kpath and Game of Thieves, which are at the same time highly descriptive and computationally affordable. Our experiments show that a strong correlation exists between WERW-Kpath and Game of Thieves and the classical centrality measures. This may suggest the po…

Theoretical computer scienceSettore INF/01 - InformaticaComputational complexity theorySocial networkComputer sciencebusiness.industryNode (networking)Complex networksComplex networkSocial network analysisK-pathBetweenness centralityCentrality measuresCorrelation coefficientsCentralitybusinessSocial network analysisClustering coefficient
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Game of Thieves and WERW-Kpath: Two Novel Measures of Node and Edge Centrality for Mafia Networks

2021

Real-world complex systems can be modeled as homogeneous or heterogeneous graphs composed by nodes connected by edges. The importance of nodes and edges is formally described by a set of measures called centralities which are typically studied for graphs of small size. The proliferation of digital collection of data has led to huge graphs with billions of nodes and edges. For this reason, we focus on two new algorithms, Game of Thieves and WERW-Kpath which are computationally-light alternatives to the canonical centrality measures such as degree, node and edge betweenness, closeness and clustering. We explore the correlation among these measures using the Spearman’s correlation coefficient …

Theoretical computer scienceSettore INF/01 - InformaticaDegree (graph theory)Computer scienceClosenessComplex networksMafia networksComplex networkCorrelationComputational complexityBetweenness centralityNode (computer science)CentralityRank (graph theory)Cluster analysisCentrality
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An Image Segmentation Algorithm based on Community Detection

2016

International audience; With the recent advances in complex networks, image segmentation becomes one of the most appropriate application areas. In this context, we propose in this paper a new perspective of image segmentation by applying two efficient community detection algorithms. By considering regions as communities, these methods can give an over-segmented image that has many small regions. So, the proposed algorithms are improved to automatically merge those neighboring regions agglomerative to achieve the highest modularity/stability. To produce sizable regions and detect homogeneous communities, we use the combination of a feature based on the Histogram of Oriented Gradients of the …

[ INFO ] Computer Science [cs]Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentation02 engineering and technology[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Minimum spanning tree-based segmentationImage texture0202 electrical engineering electronic engineering information engineeringcommunity detection[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Segmentation[INFO]Computer Science [cs][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]modularityImage segmentationSegmentation-based object categorizationbusiness.industry[ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]Pattern recognitionImage segmentationcomplex networksHistogram of oriented gradientsRegion growing020201 artificial intelligence & image processingArtificial intelligencebusiness
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On Topological Structure of Web Services Networks for Composition. In Int. Journal of Web Engineering and Technology

2013

In order to deal efficiently with the exponential growth of the Web services landscape in composition life cycle activities, it is necessary to have a clear view of its main features. As for many situations where there is a lot of interacting entities, the complex networks paradigm is an appropriate approach to analyze the interactions between the multitudes of Web services. In this paper, we present and investigate the main interactions between semantic Web services models from the complex network perspective. Results show that both parameter and operation networks exhibit the main characteristics of typical real-world complex networks such as the "small-world" property and an inhomogeneou…

[INFO.INFO-WB] Computer Science [cs]/WebInteraction networks[INFO.INFO-WB]Computer Science [cs]/WebComplex networks[ INFO.INFO-WB ] Computer Science [cs]/WebWeb servicesCompositionSemantics
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Diversity and complexity of microbial communities from a chlor-alkali tailings dump

2015

Abstract Revegetation of the tailings dumps produced by various industrial activities is necessary to prevent dust storms and erosion and represents a great challenge for ecological restoration. Little is known about the microbial colonisation and community structure of revegetated tailings following site exploitation. Here, we report the sequencing of 16S rRNA and internal transcribed spacer (ITS) fungal RNA gene amplicons from chlor-alkali residue and from an adjacent undisturbed soil to define the composition and assembly of the rhizosphere microbial communities. After quality filtering, a total of 72,373 and 89,929 bacterial sequences and 122,618 and 111,209 fungal sequences remained fo…

[SDV]Life Sciences [q-bio]Microbial networks010501 environmental sciences01 natural sciences[ SDE ] Environmental SciencesElectric network topologyHebelomaBacteria (microorganisms)ComputingMilieux_MISCELLANEOUS2. Zero hunger0303 health sciencesRhizosphereBar codingEcologyEcologySoil physico-chemical propertiesFungal communityRhizosphere microbial communitiesAnthropogenic soilsSoil typeTailingsTailings dumpSoil conservationBacterial communityGammaproteobacteriaComplex networksMicroorganismsSoil ScienceBiologyMicrobiology03 medical and health sciencesRevegetationMicrobial ecologyPseudomonasGammaproteobacteriaBotanyDominance (ecology)RevegetationEcological restoration030304 developmental biology0105 earth and related environmental sciencesBar-codingGeoporaBacteria15. Life on landbiology.organism_classificationMicrobial population biologyInternal transcribed spacers13. Climate actionRNA
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Statistical Regularities in ATM: network properties, trajectory deviations and delays

2012

One of the key enabler to the productivity and efficiency shift foreseen by SESAR will be the business-trajectory concept. The path to a deep understanding of how this new concept impacts on the future SESAR Air Traffic Management scenario goes through a better understanding of the actual air traffic network, and this will be done in the present paper by analyzing traffic data within the framework of complex network analysis. In this paper we will consider flights trajectory data from the Data Demand Repository database. In a first investigation, we perform a network study of the air traffic infrastructure starting from the airports and then refining our analysis at the level of navigation …

air traffic management complex networksSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)
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ELSA Project: Toward a complex network approach to ATM delays analysis

2011

The paper presents the preliminary results delivered by the WPE project ELSA. After some introductory notes about the project aims and structure, the paper shows how tools borrowed by the Complex Network Theory can be used to study the issue of delays in the air traffic system.

air traffic systemcomplex networks
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