@prefix dcat: <http://www.w3.org/ns/dcat#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix vcard: <http://www.w3.org/2006/vcard/ns#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-tel-00950700v1> a dcat:Dataset ;
    dct:description """
              The LHCb online system relies on a large and heterogeneous IT infrastructure made from thousands of servers on which many different applications are running. They run a great variety of tasks : critical ones such as data taking and secondary ones like web servers. The administration of such a system and making sure it is working properly represents a very important workload for the small expert-operator team. Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called “self objectives” supposed to lead to “autonomic computing”. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way Linux-based systems and their interaction with software. Moreover, the shared experience approach we use, coupled with an "object oriented paradigm" architecture increases a lot our learning speed, and highlight relations between problems.
            """ ;
    dct:identifier "NNT: 2013CLF22387" ;
    dct:issued "2026-05-06T06:51:10.065738"^^xsd:dateTime ;
    dct:language "en" ;
    dct:modified "2026-05-06T06:51:10.065743"^^xsd:dateTime ;
    dct:publisher <https://rec.harvest-normandie.data4citizen.com/organization/cce9db95-46d9-4dc2-84b6-764215d0a002> ;
    dct:title "Phronesis, a diagnosis and recovery tool for system administrators" ;
    dcat:contactPoint [ a vcard:Organization ;
            vcard:fn "CCSD" ] ;
    dcat:distribution <https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-tel-00950700v1/resource/2d6ebc1c-ce90-4ed3-844d-ad5ce8ffbc95> ;
    dcat:keyword "administration-systeme",
        "apprentissage-par-renforcement",
        "artificial-intelligence",
        "autonomic-computing",
        "cern",
        "diagnosis",
        "diagnostiques",
        "infoeu-reposemanticsdoctoralthesis",
        "infoinfo-ohcomputer-science-csother-csoh",
        "informatique-autonome",
        "intelligence-artificielle",
        "lhcb",
        "linux",
        "recouvrement",
        "recovery",
        "reinforcement-learning",
        "spiotherengineering-sciences-physicsother",
        "system-administration",
        "theses" ;
    dcat:landingPage <https://theses.hal.science/tel-00950700> .

<https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-tel-00950700v1/resource/2d6ebc1c-ce90-4ed3-844d-ad5ce8ffbc95> a dcat:Distribution ;
    dct:format "HTML" ;
    dct:issued "2026-05-06T06:51:10.105196"^^xsd:dateTime ;
    dct:modified "2026-05-06T06:51:10.035476"^^xsd:dateTime ;
    dct:title "Phronesis, a diagnosis and recovery tool for system administrators" ;
    dcat:accessURL <https://theses.hal.science/tel-00950700> .

<https://rec.harvest-normandie.data4citizen.com/organization/cce9db95-46d9-4dc2-84b6-764215d0a002> a foaf:Agent ;
    foaf:name "test_moissonnage_selune" .

<https://theses.hal.science/tel-00950700> a foaf:Document .