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Evolution of Prioritized\(\mathcal{E}\mathcal{L}\) Ontologies

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Abstract

In this paper, we place ourselves in the context of the evolution of\(\mathcal{E}\mathcal{L}\) ontologies when a new piece of information that can be uncertain is available. The\(\mathcal{E}\mathcal{L}\) is a tractable family of lightweight description logics that underlay theOWL2 EL profile. To take into consideration the weights attached to the axioms reflecting their reliability or credibility, we propose an extension of the\(\mathcal{E}\mathcal{L}\) family within the possibility theory setting. This theory provides a natural framework to deal with the ordinal scale. We show how to induce a prioritized\(\mathcal{E}\mathcal{L}\) ontology in case we start with standard ontology,i.e., axioms without weights. The explored method exploits conflict statistical analysis between axioms to induce a vector space. Finally, we propose polynomial syntactic algorithms for the evolution process while preserving the consistency of the ontology.

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Acknowledgments

This work was supported by ANR CHAIRE IA BE4musIA and FEI INS2I 2022 EMILIE.

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Authors and Affiliations

  1. University of Sfax, MIRACL Laboratory, ISIMS, Sfax, Tunisia

    Rim Mohamed, Zied Loukil & Faiez Gargouri

  2. CRIL CNRS & Univ Artois, Lens, France

    Zied Bouraoui

Authors
  1. Rim Mohamed

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  2. Zied Loukil

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  3. Faiez Gargouri

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  4. Zied Bouraoui

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Corresponding author

Correspondence toRim Mohamed.

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Editors and Affiliations

  1. i-SOMET, Inc., Morioka-shi, Iwate, Japan

    Hamido Fujita

  2. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, Guangdong, China

    Philippe Fournier-Viger

  3. Texas State University, San Marcos, TX, USA

    Moonis Ali

  4. Shanghai University of Finance and Economics, Shanghai, China

    Yinglin Wang

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Mohamed, R., Loukil, Z., Gargouri, F., Bouraoui, Z. (2022). Evolution of Prioritized\(\mathcal{E}\mathcal{L}\) Ontologies. In: Fujita, H., Fournier-Viger, P., Ali, M., Wang, Y. (eds) Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence. IEA/AIE 2022. Lecture Notes in Computer Science(), vol 13343. Springer, Cham. https://doi.org/10.1007/978-3-031-08530-7_72

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