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LinkedMDR: A Collective Knowledge Representation of a Heterogeneous Document Corpus

  • Nathalie Charbel
  • Christian Sallaberry
  • Sebastien Laborie
  • Gilbert Tekli
  • Richard Chbeir
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10438)

Abstract

The ever increasing need for extracting knowledge from heterogeneous data has become a major concern. This is particularly observed in many application domains where several actors, with different expertise, exchange a great amount of information at any stage of a large-scale project. In this paper, we propose LinkedMDR: a novel ontology for Linked Multimedia Document Representation that describes the knowledge of a heterogeneous document corpus in a semantic data network. LinkedMDR combines existing standards and introduces new components that handle the connections between these standards and augment their capabilities. It is generic and offers a pluggable layer that makes it adaptable to different domain-specific knowledge. Experiments conducted on construction projects show that LinkedMDR is applicable in real-world scenarios.

Keywords

Heterogeneous documents Document Representation Ontologies Information Retrieval 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Nathalie Charbel
    • 1
  • Christian Sallaberry
    • 2
  • Sebastien Laborie
    • 1
  • Gilbert Tekli
    • 3
  • Richard Chbeir
    • 1
  1. 1.University Pau & Pays Adour, LIUPPA, EA3000AngletFrance
  2. 2.University Pau & Pays Adour, LIUPPA, EA3000PauFrance
  3. 3.University of Balamand (UOB)TripoliLebanon

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