@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-hal-00084635v1> a dcat:Dataset ;
    dct:description """
              In this article, we apply the “EM” algorithm to learning the parameters of a Markov chain mixture model for clus-tering navigation sessions on a Web site. Our main con-tribution is to deduce the model's initial parameters from clusters formed by a hierarchical clustering of a sample of sessions, whose dissimilarity matrix is computed by Dynamic Time Warping. The states of the Markov chains are the neurons of a Kohonen Self Organizing Map, which displays the site as it is seen by the users and also clusters its pages (one neuron corresponding to a cluster of pages). This technique for clustering sessions has been validated on a set of semi-artificial data and the results are excellent. Finally, we tested several criteria for the determination of the optimal number of clusters and con-cluded that the Akaike Information Criterion was best suited to this problem.
            """ ;
    dct:identifier "hal-00084635" ;
    dct:issued "2026-05-10T07:11:50.287770"^^xsd:dateTime ;
    dct:language "en" ;
    dct:modified "2026-05-10T07:11:50.287775"^^xsd:dateTime ;
    dct:publisher <https://rec.harvest-normandie.data4citizen.com/organization/cce9db95-46d9-4dc2-84b6-764215d0a002> ;
    dct:title "Hybrid Connectionist Approach for Knowledge Discovery from Web Navigation Patterns" ;
    dcat:contactPoint [ a vcard:Organization ;
            vcard:fn "CCSD" ] ;
    dcat:distribution <https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-hal-00084635v1/resource/55ef2c69-b4e4-44da-b651-d6f4b1f4b5b9> ;
    dcat:keyword "conference-papers",
        "connectionist-learning",
        "infoeu-reposemanticsconferenceobject",
        "infoinfo-lgcomputer-science-csmachine-learning-cslg",
        "knowledge-discovery-from-web-navigation-patterns",
        "web-mining" ;
    dcat:landingPage <ACS/IEEE%20International%20Conference%20on%20Computer%20Systems%20and%20Applications> .

<ACS/IEEE%20International%20Conference%20on%20Computer%20Systems%20and%20Applications> a foaf:Document .

<https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-hal-00084635v1/resource/55ef2c69-b4e4-44da-b651-d6f4b1f4b5b9> a dcat:Distribution ;
    dct:format "HTML" ;
    dct:issued "2026-05-10T07:11:50.294697"^^xsd:dateTime ;
    dct:modified "2026-05-10T07:11:50.279780"^^xsd:dateTime ;
    dct:title "Hybrid Connectionist Approach for Knowledge Discovery from Web Navigation Patterns" ;
    dcat:accessURL <https://hal.science/hal-00084635> .

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