Modélisation ontologique des connaissances expertes pour l'analyse de comportements à risque : application à la surveillance maritime

Abstract : In our societies, where information is everywhere the capacity to capture and analyze this information is a major issue for every entity that must take a decision. From this capacity dependsthe efficiency of the actions and measures that will be undertaken. But face with the large increase of available data, the increasing number of actors and the increasing complexity of threats the strategic environment in which decision-makers operates is characterized by a significant uncertainty. This general observation is also present in the maritime domain characterised by heterogeneous threats, a large effective area and a large number of stakeholders.Therefore, this proposed research explores the potentiality of spatial ontologies for modelling, sharing and inference. The purpose is to provide a suitable environment for the experts where knowledge about abnormal maritime behaviour can be modelled. However, this knowledge is spatio-temporal. It has therefore been necessary to extend the initial functionality of the SWRL language to take into account these characteristics.Finally, the adopted approach has been had been implemented inside the OntoMap prototype. From retrieving the data to the cartographic analysis, this prototype offers all the necessary elements to understand an abnormal situation.
Document type :
Theses
Complete list of metadatas

Cited literature [226 references]  Display  Hide  Download

https://pastel.archives-ouvertes.fr/pastel-00819259
Contributor : Abes Star <>
Submitted on : Tuesday, April 30, 2013 - 3:38:08 PM
Last modification on : Monday, November 12, 2018 - 11:00:31 AM
Long-term archiving on : Wednesday, July 31, 2013 - 4:07:51 AM

File

2012ENMP0077.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : pastel-00819259, version 1

Citation

Arnaud Vandecasteele. Modélisation ontologique des connaissances expertes pour l'analyse de comportements à risque : application à la surveillance maritime. Economies et finances. Ecole Nationale Supérieure des Mines de Paris, 2012. Français. ⟨NNT : 2012ENMP0077⟩. ⟨pastel-00819259⟩

Share

Metrics

Record views

1149

Files downloads

5174