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|Title:||LinkedMDR: a collective knowledge representation of a heterogeneous document corpus||Authors:||Charbel, Nathalie
|Affiliations:||Department of Mechatronics Engineering||Keywords:||Heterogeneous documents
|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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