Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/661
Title: LinkedMDR : A Collective Knowledge Representation of a Heterogeneous Document Corpus
Authors: Charbel, Nathalie
Sallaberry, Christian
Laborie, Sebastien
Tekli, Gilbert 
Chbeir, Richard
Affiliations: Department of Mechatronics Engineering 
Keywords: Heterogeneous documents
Document Representation
Subjects: Ontologie
Information retrieval
Issue Date: 2017
Publisher: Springer
Part of: Database and Expert Systems Applications : 28th International Conference, DEXA 2017, Lyon, France, August 28-31, 2017, Proceedings, Part I
Start page: 362
End page: 377
Conference: International Conference on Database and Expert Systems Applications (28-31 August 2017 : Lyon, France) 
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.
URI: https://scholarhub.balamand.edu.lb/handle/uob/661
Ezproxy URL: Link to full text
Type: Conference Paper
Appears in Collections:Department of Mechatronics Engineering

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