Search results for "big data."

showing 10 items of 310 documents

Development of multivariate and network models for the analysis of Big Data: applications in economics, insurance, and social sciences

2020

In questa tesi sviluppo metodi statistici multivariati e di rete per lo studio di sistemi complessi. In particolare, focalizzo la mia analisi sullo studio di reti complesse bipartite e le loro applicazioni a (i) l'economia, per capire l'effetto di contagio tra istituti finanziari e stati sovrani, (ii) la sorveglianza nelle assicurazioni, per individuare comportamenti fraudolenti, e (iii) le scienze sociali, per studiare l'effetto delle politiche del REF sulle eccellenze nella ricerca delle università in UK. In this thesis I develop multivariate statistical and network methods for the study of complex systems. In particular, I focus my analysis on the study of bipartite complex networks and …

Big DataSettore SECS-S/06 -Metodi Mat. dell'Economia e d. Scienze Attuariali e Finanz.Complex SystemBipartite Complex Network
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Modelling and development of a generic observatory to harvest and analyze big data

2021

Big Data fascinate, both because of the value they hold that can provide a significant advantage in decision-making, and because of the challenges that their exploitation represents. These challenges are present at several levels of analytics workflows. At the level of the creation of software architectures, the volume and the velocity require at least enough performance to handle the ingestion and storage of data. The data variety has also an impact, as several new storage systems have emerged, each one corresponding to a specific need. The polystores are systems that integrate this diversity, to gain flexibility compared to the data warehouses, now too rigid. However, this diversification…

Big DataStream processing[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]TenseursData modelsCategory TheoryArchitectures logiciellesTensorsThéorie des catégoriesDonnées massivesModèles de donnéesSoftware Architectures
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Deep learning and process understanding for data-driven Earth system science

2017

Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, rather than amending classical machine learning, we argue that these contextual cues should be used as part of deep learning (an approach that is able to extract spatio-temporal features automatically) to gain further process understanding of Earth system science problems, improving the predictive ability of seasonal forecasting and modelling of long-range spatial connections across multiple timescales, for example. The next step will be a hybri…

Big DataTime FactorsProcess modelingGeospatial analysis010504 meteorology & atmospheric sciencesProcess (engineering)0208 environmental biotechnologyBig dataGeographic Mapping02 engineering and technologycomputer.software_genreMachine learning01 natural sciencesPattern Recognition AutomatedData-drivenDeep LearningSpatio-Temporal AnalysisHumansComputer SimulationWeather0105 earth and related environmental sciencesMultidisciplinarybusiness.industryDeep learningUncertaintyReproducibility of ResultsTranslatingRegression Psychology020801 environmental engineeringEarth system scienceKnowledgePattern recognition (psychology)Earth SciencesFemaleSeasonsArtificial intelligencebusinessPsychologyFacial RecognitioncomputerForecastingNature
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On Big Data: How should we make sense of them?

2020

The topic of Big Data is today extensively discussed, not only on the technical ground. This also depends on the fact that Big Data are frequently presented as allowing an epistemological paradigm shift in scientific research, which would be able to supersede the traditional hypothesis-driven method. In this piece, I critically scrutinize two key claims that are usually associated with this approach, namely, the fact that data speak for themselves, deflating the role of theories and models, and the primacy of correlation over causation. In so doing, I will also refer to a recent case history of data mining projects in the field of biomedicine, i.e. EXPOsOMICS. My intention is both to acknow…

Big DataValue (ethics)causalityMultidisciplinarydata-driven scienceComputer sciencebusiness.industryBig dataepistemologyopacity of algorithm.Data scienceend of theoryHistory and Philosophy of ScienceParadigm shiftKey (cryptography)CausationHeuristicsbusinessMètode Revista de difusió de la investigació
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Choosing Optimal Seed Nodes in Competitive Contagion.

2019

International audience; In recent years there has been a growing interest in simulating competitive markets to find out the efficient ways to advertise a product or spread an ideology. Along this line, we consider a binary competitive contagion process where two infections, A and B, interact with each other and diffuse simultaneously in a network. We investigate which is the best centrality measure to find out the seed nodes a company should adopt in the presence of rivals so that it can maximize its influence. These nodes can be used as the initial spreaders or advertisers by firms when two firms compete with each other. Each node is assigned a price tag to become an initial advertiser whi…

Big Datagame theoryComputer scienceProcess (engineering)01 natural sciencescompetitive contagionMicroeconomics010104 statistics & probabilityArtificial IntelligenceNode (computer science)Computer Science (miscellaneous)seed nodes0101 mathematicsOriginal ResearchSmall numbercentrality measures010102 general mathematicsStochastic game[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]complex networksComplex networkProduct (business)CentralityGame theorycompetitive marketingInformation SystemsFrontiers in big data
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Massadatan hyödyntämisen menestystekijät ja haasteet digitaalisessa markkinoinnissa

2017

Tämä kandidaatintutkielma tutkii menestystekijöitä massadatan hyödyntämisessä digitaalisen markkinoinnin tarkoituksiin. Yleisesti aihepiiriä on aiemmin tutkittu lähinnä koko liiketoiminnan näkökulmasta. Tutkielma pyrkii selvittämään näkökulmia aihepiiriin juuri markkinoinnin kannalta, sillä markkinoinnin näkökulmasta aihetta ei ole tutkittu kovin laajasti. Tutkielma on toteutettu kirjallisuuskatsauksena. Suurin osa lähdeaineistosta on viime vuosilta, ja varsinkin markkinoinnin näkökulmasta tehty massadatan hyödyntämisen tutkimus on tuoretta. Lähdeaineisto koostuu pääasiassa vertaisarvioiduista tieteellisistä artikkeleista. Myös kaupallisia lähteitä on käytetty suhteellisen paljon, sillä tut…

Big DatamarkkinointiBImassadatamenestystekijätdigitaalinen markkinointi
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Variation in end-of-life care and hospital palliative care among hospitals and local authorities: A preliminary contribution of big data.

2021

Background: Many studies explore the clinical and ethical dimensions of care at the end-of-life, but fewer use administrative data to examine individual and geographic differences, including the use of palliative care. Aim: Provide a population-based perspective on end-of-life and hospital palliative care among local authorities and hospitals in France. Design: Retrospective cohort study of care received by 17,928 decedents 65 and over (last 6 months of life), using the French national health insurance database Results: 55.7% of decedents died in acute-care hospitals; 79% were hospitalized in them at least once; 11.7% were admitted at least once for hospital palliative care. Among 31 academ…

Big Datamedicine.medical_specialtyPalliative care[SDV]Life Sciences [q-bio]Big dataGeographic variationgeographic variation03 medical and health sciences0302 clinical medicinemedicineHumans030212 general & internal medicineRetrospective StudiesTerminal Carebusiness.industryPalliative CareGeneral Medicineodds of admissionHospitals3. Good healthAnesthesiology and Pain MedicineVariation (linguistics)030220 oncology & carcinogenesisFamily medicinebusinessEnd-of-life careEnd-of-lifePalliative medicine
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Tiedonkeruun hallinta esineiden internetissä

2016

Digitalisaatio tuo tullessaan suuria muutoksia käsitykseemme koneiden ja ihmisten vuorovaikutuksesta. Tämä vuorovaikutus syntyy erilaisten tietolähteiden tuottaman tiedon kautta. Tässä tutkielmassa tarkastellaan millaista tietoa tuotetaan ja miten suuria määriä numeerista tietoa tulisi tuottaa, jotta se olisi myöhäisemmässä vaiheessa käyttökelpoista. Digitalization brings major changes in the understanding about interactions between machines and humans. This interaction is created through knowledge of various sources of information produced. This thesis examines what information is produced and how large amounts of numerical data should produce in order to be useful at a later stage.

Big DatatiedonkeruutiedonhallintaEsineiden ja asioiden internetteollinen internettiedonkäsittely
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Towards Service-oriented 5G: Virtualizing the Networks for Everything-as-a-Service

2018

It is widely acknowledged that the forthcoming 5G architecture will be highly heterogeneous and deployed with a high degree of density. These changes over the current 4G bring many challenges on how to achieve an efficient operation from the network management perspective. In this article, we introduce a revolutionary vision of the future 5G wireless networks, in which the network is no longer limited by hardware or even software. Specifically, by the idea of virtualizing the wireless networks, which has recently gained increasing attention, we introduce the Everything-as-a-Service (XaaS) taxonomy to light the way towards designing the service-oriented wireless networks. The concepts, chall…

Big Datawireless networksNetworking and Internet Architecture (cs.NI)FOS: Computer and information sciencesvirtualisointisoftware5G-tekniikkawireless network virtualizationEverything-as-a-servicevirtualizationComputer Science - Networking and Internet Architecture5G technologyvirtualisation5G mobile communicationhardwarelcsh:Electrical engineering. Electronics. Nuclear engineeringeverything-as-a-servicecomputer architecturelcsh:TK1-99715Glangattomat verkot
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BIG DATA, COMPETITION AND PRIVACY: A LOOK FROM THE ANTITRUST PERSPECTIVE

2016

de spesso confrontarsi due diverse « visioni del mondo ». Da un lato, i big data sono descritti come un input essenziale controllato da imprese dominanti, che costituisce una barriera all entrata, consolida le posizioni di mercato e consente pratiche commerciali a danno dei consumatori. Dall altro lato, i big data sono descritti come una commodity, un input che può essere acquisito attraverso una molteplicità di mezzi e che consente alle imprese di offrire ai consumatori servizi innovativi. La lettura del rapporto tra big data e concorrenza attraverso le lenti tipiche dell analisi antitrust suggerisce che queste due visioni del mondo non costituiscono due modelli teorici da valutare in astr…

Big data - competition law
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