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Semantic Representation of a Heterogeneous Document Corpus for an Innovative Information Retrieval Model: Application to the Construction Industry Nathalie CHARBELInformation Retrieval [cs.IR]. Université de Pau et des Pays de l'Adour, 2018. English. ⟨NNT : ⟩
Theses
tel-02074440v1
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Semantic Representation of a Heterogeneous Document Corpus for an Innovative Information Retrieval Model : Application to the Construction IndustryMultimedia [cs.MM]. LIUPPA - Laboratoire Informatique de l'Université de Pau et des Pays de l'Adour, 2018. English. ⟨NNT : 2018PAUU3025⟩
Theses
tel-02465630v1
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LinkedMDR: A Collective Knowledge Representation of a Heterogeneous Document CorpusThe 28th International Conference on Database and Expert Systems Applications (DEXA 2017), Aug 2017, Lyon, France. pp.362-377, ⟨10.1007/978-3-319-64468-4_28⟩
Conference papers
hal-01817333v1
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XSDF: A System for XML Semantic Disambiguation2015 1st International Conference on Applied Research in Computer Science and Engineering, ICAR 2015, Oct 2015, Beirut, Lebanon. ⟨10.1109/ARCSE.2015.7338130⟩
Conference papers
hal-01909105v1
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LinkedMDR: un modèle sémantique de représentation de corpus de documents multimédia35ème congrès INFormatique des ORganisations et Systèmes d’Information et de Décision (INFORSID 2017), May 2017, Toulouse, France. pp.11-26
Conference papers
hal-01553840v1
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Hybrid Molecule-based Information RetrievalThe 34th ACM/SIGAPP Symposium On Applied Computing (ACM SAC 2019), Apr 2019, Limassol, Cyprus. pp.808-815, ⟨10.1145/3297280.3297358⟩
Conference papers
hal-02077488v1
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