LinkedMDR: A Collective Knowledge Representation of a Heterogeneous Document Corpus
Overview & Synopsis
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.
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Document Information
| Document Title | LinkedMDR: A Collective Knowledge Representation of a Heterogeneous Document Corpus |
|---|---|
| Author / Organization | Nathalie Charbel, Christian Sallaberry, Sébastien Laborie, Gilbert Tekli, Richard Chbeir |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2017 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-199824 |
| Original Source Link | Visit Source Page on hal.science » |