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Semantic context consolidation and rule learning for optimized transport assignments in hospitals

Femke Ongenae (UGent) , Pieter Bonte (UGent) , Jeroen Schaballie (UGent) , Bert Vankeirsbilck (UGent) and Filip De Turck (UGent)
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Abstract
The increase of ICT infrastructure in hospitals offer opportunities for cost reduction by optimizing workflows, while maintaining quality of care. This work-in-progress poster details the AORTA system, which is a semantic platform to optimize transportation task scheduling and execution in hospitals. It provides a dynamic scheduler with an upto-date view about the current context by performing semantic reasoning on the information provided by the available software tools and smart devices. Additionally, it learns semantic rules based on historical data in order to avoid future delays in transportation time.
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Citation

Please use this url to cite or link to this publication:

Chicago
Ongenae, Femke, Pieter Bonte, Jeroen Schaballie, Bert Vankeirsbilck, and Filip De Turck. 2016. “Semantic Context Consolidation and Rule Learning for Optimized Transport Assignments in Hospitals.” In SEMANTIC WEB, ESWC 2016 , 9989:88–92. Springer Nature.
APA
Ongenae, F., Bonte, P., Schaballie, J., Vankeirsbilck, B., & De Turck, F. (2016). Semantic context consolidation and rule learning for optimized transport assignments in hospitals. SEMANTIC WEB, ESWC 2016 (Vol. 9989, pp. 88–92). Presented at the 13th European Semantic Web Conference (ESWC) , Springer Nature.
Vancouver
1.
Ongenae F, Bonte P, Schaballie J, Vankeirsbilck B, De Turck F. Semantic context consolidation and rule learning for optimized transport assignments in hospitals. SEMANTIC WEB, ESWC 2016 . Springer Nature; 2016. p. 88–92.
MLA
Ongenae, Femke et al. “Semantic Context Consolidation and Rule Learning for Optimized Transport Assignments in Hospitals.” SEMANTIC WEB, ESWC 2016 . Vol. 9989. Springer Nature, 2016. 88–92. Print.
@inproceedings{8500134,
  abstract     = {The increase of ICT infrastructure in hospitals offer opportunities for cost reduction by optimizing workflows, while maintaining quality of care. This work-in-progress poster details the AORTA system, which is a semantic platform to optimize transportation task scheduling and execution in hospitals. It provides a dynamic scheduler with an upto-date view about the current context by performing semantic reasoning on the information provided by the available software tools and smart devices. Additionally, it learns semantic rules based on historical data in order to avoid future delays in transportation time.},
  author       = {Ongenae, Femke and Bonte, Pieter and Schaballie, Jeroen and Vankeirsbilck, Bert and De Turck, Filip},
  booktitle    = {SEMANTIC WEB, ESWC 2016 },
  isbn         = {978-3-319-47601-8},
  issn         = {0302-9743},
  keywords     = {IBCN},
  language     = {eng},
  location     = {Heraklion, Greece},
  pages        = {88--92},
  publisher    = {Springer Nature},
  title        = {Semantic context consolidation and rule learning for optimized transport assignments in hospitals},
  url          = {http://dx.doi.org/10.1007/978-3-319-47602-5_19},
  volume       = {9989},
  year         = {2016},
}

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