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Prévision de liens dans des grands graphes de terrain (application aux réseaux bibliographiques)

Author: Manisha PujariCéline RouveirolAldo GangemiCéline RobardetBénédicte Le Grand, chercheuse en informatique).All authors
Publisher: 2015.
Dissertation: Thèse de doctorat : Informatique : Sorbonne Paris Cité : 2015.
Edition/Format:   Computer file : Document : Thesis/dissertation : English
Summary:
Nous nous intéressons dans ce travail au problème de prévision de nouveaux liens dans des grands graphes de terrain. Nous explorons en particulier les approches topologiques dyadiques pour la prévision de liens. Différentes mesures de proximité topologique ont été étudiées dans la littérature pour prédire l'apparition de nouveaux liens. Des techniques d'apprentissage supervisé ont été aussi utilisées
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Details

Genre/Form: Thèses et écrits académiques
Material Type: Document, Thesis/dissertation, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Manisha Pujari; Céline Rouveirol; Aldo Gangemi; Céline Robardet; Bénédicte Le Grand, chercheuse en informatique).; Rushed Kanawati, chercheur en informatique).; Christophe Prieur, auteur en sciences et techniques).; Université Sorbonne Paris Cité.; École doctorale Galilée (Villetaneuse, Seine-Saint-Denis).; Université Paris 13.; Laboratoire informatique de Paris-Nord (Villetaneuse, Seine-Saint-Denis).
OCLC Number: 976436550
Notes: Titre provenant de l'écran-titre.
Description: 1 online resource
Responsibility: Manisha Pujari ; sous la direction de Céline Rouveirol.

Abstract:

Nous nous intéressons dans ce travail au problème de prévision de nouveaux liens dans des grands graphes de terrain. Nous explorons en particulier les approches topologiques dyadiques pour la prévision de liens. Différentes mesures de proximité topologique ont été étudiées dans la littérature pour prédire l'apparition de nouveaux liens. Des techniques d'apprentissage supervisé ont été aussi utilisées afin de combiner ces différentes mesures pour construire des modèles prédictifs. Le problème d'apprentissage supervisé est ici un problème difficile à cause notamment du fort déséquilibre de classes. Dans cette thèse, nous explorons différentes approches alternatives pour améliorer les performances des approches dyadiques pour la prévision de liens. Nous proposons d'abord, une approche originale de combinaison des prévisions fondée sur des techniques d'agrégation supervisée de listes triées (ou agrégation de préférences). Nous explorons aussi différentes approches pour améliorer les performances des approches supervisées pour la prévision de liens. Une première approche consiste à étendre l'ensemble des attributs décrivant un exemple (paires de noeuds) par des attributs calculés dans un réseau multiplexe qui englobe le réseau cible. Un deuxième axe consiste à évaluer l'apport destechniques de détection de communautés pour l'échantillonnage des exemples. Des expérimentations menées sur des réseaux réels extraits de la base bibliographique DBLP montrent l'intérêt des approaches proposées.

In this work, we are interested to tackle the problem of link prediction in complex networks. In particular, we explore topological dyadic approaches for link prediction. Different topological proximity measures have been studied in the scientific literature for finding the probability of appearance of new links in a complex network. Supervided learning methods have also been used to combine the predictions made or information provided by different topological measures. The create predictive models using various topological measures. The problem of supervised learning for link prediction is a difficult problem especially due to the presence of heavy class imbalance. In this thesis, we search different alternative approaches to improve the performance of different dyadic approaches for link prediction. We propose here, a new approach of link prediction based on supervised rank agregation that uses concepts from computational social choice theory. Our approach is founded on supervised techniques of aggregating sorted lists (or preference aggregation). We also explore different ways of improving supervised link prediction approaches. One approach is to extend the set of attributes describing an example (pair of nodes) by attributes calculated in a multiplex network that includes the target network. Multiplex networks have a layered structure, each layer having different kinds of links between same sets of nodes. The second way is to use community information for sampling of examples to deal with the problem of classe imabalance. Experiments conducted on real networks extracted from well known DBLP bibliographic database.

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Linked Data


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Primary Entity<\/h3>\n
<http:\/\/www.worldcat.org\/oclc\/976436550<\/a>> # Pr\u00E9vision de liens dans des grands graphes de terrain (application aux r\u00E9seaux bibliographiques)<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:CreativeWork<\/a>, bgn:ComputerFile<\/a>, bgn:Thesis<\/a>, schema:MediaObject<\/a> ;\u00A0\u00A0\u00A0\nbgn:inSupportOf<\/a> \"Th\u00E8se de doctorat : Informatique : Sorbonne Paris Cit\u00E9 : 2015.<\/span>\" ;\u00A0\u00A0\u00A0\nlibrary:oclcnum<\/a> \"976436550<\/span>\" ;\u00A0\u00A0\u00A0\nlibrary:placeOfPublication<\/a> <http:\/\/id.loc.gov\/vocabulary\/countries\/fr<\/a>> ;\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Thing\/agregation_supervisee_de_preferences<\/a>> ; # Agr\u00E9gation supervis\u00E9e de pr\u00E9f\u00E9rences<\/span>\n\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Thing\/reseaux_complexes<\/a>> ; # R\u00E9seaux complexes<\/span>\n\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Thing\/analyse_de_reseaux_multiplexes<\/a>> ; # Analyse de r\u00E9seaux multiplexes<\/span>\n\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Topic\/multiplexage<\/a>> ; # Multiplexage<\/span>\n\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Thing\/previsions_de_liens<\/a>> ; # Pr\u00E9visions de liens<\/span>\n\u00A0\u00A0\u00A0\nschema:author<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/pujari_manisha_1982<\/a>> ; # Manisha Pujari<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/gangemi_aldo<\/a>> ; # Aldo Gangemi<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Organization\/universite_paris_13<\/a>> ; # Universit\u00E9 Paris 13.<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/kanawati_rushed_19_chercheur_en_informatique<\/a>> ; # chercheur en informatique). Rushed Kanawati<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/prieur_christophe_19_auteur_en_sciences_et_techniques<\/a>> ; # auteur en sciences et techniques). Christophe Prieur<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Organization\/laboratoire_informatique_de_paris_nord_villetaneuse_seine_saint_denis<\/a>> ; # Laboratoire informatique de Paris-Nord (Villetaneuse, Seine-Saint-Denis).<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Organization\/universite_sorbonne_paris_cite<\/a>> ; # Universit\u00E9 Sorbonne Paris Cit\u00E9.<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/rouveirol_celine<\/a>> ; # C\u00E9line Rouveirol<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/le_grand_benedicte_1975_chercheuse_en_informatique<\/a>> ; # chercheuse en informatique). B\u00E9n\u00E9dicte Le Grand<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Organization\/ecole_doctorale_galilee_villetaneuse_seine_saint_denis<\/a>> ; # \u00C9cole doctorale Galil\u00E9e (Villetaneuse, Seine-Saint-Denis).<\/span>\n\u00A0\u00A0\u00A0\nschema:contributor<\/a> <http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/robardet_celine_1975<\/a>> ; # C\u00E9line Robardet<\/span>\n\u00A0\u00A0\u00A0\nschema:datePublished<\/a> \"2015<\/span>\" ;\u00A0\u00A0\u00A0\nschema:description<\/a> \"In this work, we are interested to tackle the problem of link prediction in complex networks. In particular, we explore topological dyadic approaches for link prediction. Different topological proximity measures have been studied in the scientific literature for finding the probability of appearance of new links in a complex network. Supervided learning methods have also been used to combine the predictions made or information provided by different topological measures. The create predictive models using various topological measures. The problem of supervised learning for link prediction is a difficult problem especially due to the presence of heavy class imbalance. In this thesis, we search different alternative approaches to improve the performance of different dyadic approaches for link prediction. We propose here, a new approach of link prediction based on supervised rank agregation that uses concepts from computational social choice theory. Our approach is founded on supervised techniques of aggregating sorted lists (or preference aggregation). We also explore different ways of improving supervised link prediction approaches. One approach is to extend the set of attributes describing an example (pair of nodes) by attributes calculated in a multiplex network that includes the target network. Multiplex networks have a layered structure, each layer having different kinds of links between same sets of nodes. The second way is to use community information for sampling of examples to deal with the problem of classe imabalance. Experiments conducted on real networks extracted from well known DBLP bibliographic database.<\/span>\" ;\u00A0\u00A0\u00A0\nschema:description<\/a> \"Nous nous int\u00E9ressons dans ce travail au probl\u00E8me de pr\u00E9vision de nouveaux liens dans des grands graphes de terrain. Nous explorons en particulier les approches topologiques dyadiques pour la pr\u00E9vision de liens. Diff\u00E9rentes mesures de proximit\u00E9 topologique ont \u00E9t\u00E9 \u00E9tudi\u00E9es dans la litt\u00E9rature pour pr\u00E9dire l\'apparition de nouveaux liens. Des techniques d\'apprentissage supervis\u00E9 ont \u00E9t\u00E9 aussi utilis\u00E9es afin de combiner ces diff\u00E9rentes mesures pour construire des mod\u00E8les pr\u00E9dictifs. Le probl\u00E8me d\'apprentissage supervis\u00E9 est ici un probl\u00E8me difficile \u00E0 cause notamment du fort d\u00E9s\u00E9quilibre de classes. Dans cette th\u00E8se, nous explorons diff\u00E9rentes approches alternatives pour am\u00E9liorer les performances des approches dyadiques pour la pr\u00E9vision de liens. Nous proposons d\'abord, une approche originale de combinaison des pr\u00E9visions fond\u00E9e sur des techniques d\'agr\u00E9gation supervis\u00E9e de listes tri\u00E9es (ou agr\u00E9gation de pr\u00E9f\u00E9rences). Nous explorons aussi diff\u00E9rentes approches pour am\u00E9liorer les performances des approches supervis\u00E9es pour la pr\u00E9vision de liens. Une premi\u00E8re approche consiste \u00E0 \u00E9tendre l\'ensemble des attributs d\u00E9crivant un exemple (paires de noeuds) par des attributs calcul\u00E9s dans un r\u00E9seau multiplexe qui englobe le r\u00E9seau cible. Un deuxi\u00E8me axe consiste \u00E0 \u00E9valuer l\'apport destechniques de d\u00E9tection de communaut\u00E9s pour l\'\u00E9chantillonnage des exemples. Des exp\u00E9rimentations men\u00E9es sur des r\u00E9seaux r\u00E9els extraits de la base bibliographique DBLP montrent l\'int\u00E9r\u00EAt des approaches propos\u00E9es.<\/span>\" ;\u00A0\u00A0\u00A0\nschema:exampleOfWork<\/a> <http:\/\/worldcat.org\/entity\/work\/id\/4130462131<\/a>> ;\u00A0\u00A0\u00A0\nschema:genre<\/a> \"Th\u00E8ses et \u00E9crits acad\u00E9miques<\/span>\" ;\u00A0\u00A0\u00A0\nschema:inLanguage<\/a> \"en<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Pr\u00E9vision de liens dans des grands graphes de terrain (application aux r\u00E9seaux bibliographiques)<\/span>\" ;\u00A0\u00A0\u00A0\nschema:productID<\/a> \"976436550<\/span>\" ;\u00A0\u00A0\u00A0\nschema:url<\/a> <https:\/\/tel.archives-ouvertes.fr\/tel-01492938<\/a>> ;\u00A0\u00A0\u00A0\nschema:url<\/a> <http:\/\/www.theses.fr\/2015USPCD010\/document<\/a>> ;\u00A0\u00A0\u00A0\nschema:url<\/a> <http:\/\/www.theses.fr\/2015USPCD010\/abes<\/a>> ;\u00A0\u00A0\u00A0\nwdrs:describedby<\/a> <http:\/\/www.worldcat.org\/title\/-\/oclc\/976436550<\/a>> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n\n

Related Entities<\/h3>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Organization\/ecole_doctorale_galilee_villetaneuse_seine_saint_denis<\/a>> # \u00C9cole doctorale Galil\u00E9e (Villetaneuse, Seine-Saint-Denis).<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Organization<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"\u00C9cole doctorale Galil\u00E9e (Villetaneuse, Seine-Saint-Denis).<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Organization\/laboratoire_informatique_de_paris_nord_villetaneuse_seine_saint_denis<\/a>> # Laboratoire informatique de Paris-Nord (Villetaneuse, Seine-Saint-Denis).<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Organization<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Laboratoire informatique de Paris-Nord (Villetaneuse, Seine-Saint-Denis).<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Organization\/universite_paris_13<\/a>> # Universit\u00E9 Paris 13.<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Organization<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Universit\u00E9 Paris 13.<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Organization\/universite_sorbonne_paris_cite<\/a>> # Universit\u00E9 Sorbonne Paris Cit\u00E9.<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Organization<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Universit\u00E9 Sorbonne Paris Cit\u00E9.<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/gangemi_aldo<\/a>> # Aldo Gangemi<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Gangemi<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"Aldo<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Aldo Gangemi<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/kanawati_rushed_19_chercheur_en_informatique<\/a>> # chercheur en informatique). Rushed Kanawati<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:birthDate<\/a> \"19..<\/span>\" ;\u00A0\u00A0\u00A0\nschema:deathDate<\/a> \";<\/span>\" ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Kanawati<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"Rushed<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"chercheur en informatique). Rushed Kanawati<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/le_grand_benedicte_1975_chercheuse_en_informatique<\/a>> # chercheuse en informatique). B\u00E9n\u00E9dicte Le Grand<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:birthDate<\/a> \"1975<\/span>\" ;\u00A0\u00A0\u00A0\nschema:deathDate<\/a> \";<\/span>\" ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Le Grand<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"B\u00E9n\u00E9dicte<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"chercheuse en informatique). B\u00E9n\u00E9dicte Le Grand<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/prieur_christophe_19_auteur_en_sciences_et_techniques<\/a>> # auteur en sciences et techniques). Christophe Prieur<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:birthDate<\/a> \"19..<\/span>\" ;\u00A0\u00A0\u00A0\nschema:deathDate<\/a> \";<\/span>\" ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Prieur<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"Christophe<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"auteur en sciences et techniques). Christophe Prieur<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/pujari_manisha_1982<\/a>> # Manisha Pujari<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:birthDate<\/a> \"1982<\/span>\" ;\u00A0\u00A0\u00A0\nschema:deathDate<\/a> \"\" ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Pujari<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"Manisha<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Manisha Pujari<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/robardet_celine_1975<\/a>> # C\u00E9line Robardet<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:birthDate<\/a> \"1975<\/span>\" ;\u00A0\u00A0\u00A0\nschema:deathDate<\/a> \"\" ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Robardet<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"C\u00E9line<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"C\u00E9line Robardet<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Person\/rouveirol_celine<\/a>> # C\u00E9line Rouveirol<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Person<\/a> ;\u00A0\u00A0\u00A0\nschema:familyName<\/a> \"Rouveirol<\/span>\" ;\u00A0\u00A0\u00A0\nschema:givenName<\/a> \"C\u00E9line<\/span>\" ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"C\u00E9line Rouveirol<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Thing\/agregation_supervisee_de_preferences<\/a>> # Agr\u00E9gation supervis\u00E9e de pr\u00E9f\u00E9rences<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Thing<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Agr\u00E9gation supervis\u00E9e de pr\u00E9f\u00E9rences<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Thing\/analyse_de_reseaux_multiplexes<\/a>> # Analyse de r\u00E9seaux multiplexes<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Thing<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Analyse de r\u00E9seaux multiplexes<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Thing\/previsions_de_liens<\/a>> # Pr\u00E9visions de liens<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Thing<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Pr\u00E9visions de liens<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Thing\/reseaux_complexes<\/a>> # R\u00E9seaux complexes<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Thing<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"R\u00E9seaux complexes<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/experiment.worldcat.org\/entity\/work\/data\/4130462131#Topic\/multiplexage<\/a>> # Multiplexage<\/span>\n\u00A0\u00A0\u00A0\u00A0a \nschema:Intangible<\/a> ;\u00A0\u00A0\u00A0\nschema:name<\/a> \"Multiplexage<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/id.loc.gov\/vocabulary\/countries\/fr<\/a>>\u00A0\u00A0\u00A0\u00A0a \nschema:Place<\/a> ;\u00A0\u00A0\u00A0\ndcterms:identifier<\/a> \"fr<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/www.theses.fr\/2015USPCD010\/document<\/a>>\u00A0\u00A0\u00A0\nrdfs:comment<\/a> \"Acc\u00E8s au texte int\u00E9gral<\/span>\" ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n
<http:\/\/www.worldcat.org\/title\/-\/oclc\/976436550<\/a>>\u00A0\u00A0\u00A0\u00A0a \ngenont:InformationResource<\/a>, genont:ContentTypeGenericResource<\/a> ;\u00A0\u00A0\u00A0\nschema:about<\/a> <http:\/\/www.worldcat.org\/oclc\/976436550<\/a>> ; # Pr\u00E9vision de liens dans des grands graphes de terrain (application aux r\u00E9seaux bibliographiques)<\/span>\n\u00A0\u00A0\u00A0\nschema:dateModified<\/a> \"2021-02-17<\/span>\" ;\u00A0\u00A0\u00A0\nvoid:inDataset<\/a> <http:\/\/purl.oclc.org\/dataset\/WorldCat<\/a>> ;\u00A0\u00A0\u00A0\u00A0.\n\n\n<\/div>\n\n

Content-negotiable representations<\/p>\n