Zhu, L., Shen, J., & Gartner, G. (2021). Ontology-driven context-aware recommendation method for indoor navigation in large hospitals. In A. Basiri, G. Gartner, & H. Huang (Eds.), LBS 2021: Proceedings of the 16th International Conference on Location Based Services (pp. 23–26). https://doi.org/10.34726/1747
Navigating in complex and dynamic indoor spaces of large hospitals
is challenging. Since improving efficiency is a common goal for hospitals,
there is an urgent need for an accurate and personalized service recommendation
method in hospital navigation. To address this challenge, we
propose a context-aware recommendation method for personalized hospital
navigation. Firstly, an ontology-based contextual framework is designed for
hospital navigation using Protégé Web Ontology Language (OWL)-2. Then
rule-based contextual reasoning and information recommendation using
Semantic Web Rule Language (SWRL) are proposed to overcome the limitations
of ontology reasoning. Finally, some case queries are conducted using
RDF Query Language (SPARQL) to evaluate the usability of the contextual
ontology and rules.
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Project (external):
National Key R&D Program of China National Natural Science Foundation of China (NSFC) Postgraduate Research and Practice Innovation Program of Jiangsu Province China Scholarship Council (CSC)
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Project ID:
2021YFE0112300 41871371 KYCX21_1350 201906860035
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Additional information:
Published in “Proceedings of the 16th International Conference on
Location Based Services (LBS 2021)”, edited by Anahid Basiri, Georg
Gartner and Haosheng Huang, LBS 2021, 24-25 November 2021,
Glasgow, UK/online.
CC BY 4.0
