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Authors: Julie Bu Daher 1 ; Tom Huygue 1 ; Nathalie Hernandez 2 and Patricia Stolf 2

Affiliations: 1 IRIT, Université de Toulouse, CNRS, Toulouse INP, UT3, Toulouse, France ; 2 IRIT, Université de Toulouse, CNRS, Toulouse INP, UT3, UT2, Toulouse, France

Keyword(s): Semantic Web, Crisis Management, Knowledge Management, Information Inference.

Abstract: Natural crises are dangerous events that can threaten lives and lead to severe damages. Crisis-related data can be heterogeneous and be provided from multiple data sources. These data can be formally described using ontologies and then integrated and structured forming knowledge graphs. Inferring new information from knowledge graphs can strongly assist in the various phases of the crisis management process. Different approaches exist in the literature for inferring new information from knowledge graphs. In this paper, we present a case study of a flood crisis where we discuss three approaches for inferring flood-related information, and we experimentally evaluate these approaches using real flood-related data and synthetic data for further analysis. We discuss the interest of using each of these approaches and detail its advantages as well as its limitations.

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Paper citation in several formats:
Bu Daher, J.; Huygue, T.; Hernandez, N. and Stolf, P. (2022). Inferring New Information from a Knowledge Graph in Crisis Management: A Case Study. In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KEOD; ISBN 978-989-758-614-9; ISSN 2184-3228, SciTePress, pages 43-54. DOI: 10.5220/0011511200003335

@conference{keod22,
author={Julie {Bu Daher}. and Tom Huygue. and Nathalie Hernandez. and Patricia Stolf.},
title={Inferring New Information from a Knowledge Graph in Crisis Management: A Case Study},
booktitle={Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KEOD},
year={2022},
pages={43-54},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011511200003335},
isbn={978-989-758-614-9},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2022) - KEOD
TI - Inferring New Information from a Knowledge Graph in Crisis Management: A Case Study
SN - 978-989-758-614-9
IS - 2184-3228
AU - Bu Daher, J.
AU - Huygue, T.
AU - Hernandez, N.
AU - Stolf, P.
PY - 2022
SP - 43
EP - 54
DO - 10.5220/0011511200003335
PB - SciTePress

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