A semi-automatic framework towards building Electricity Grid Infrastructure Management ontology: A case study and retrospective
Résumé
Thanks to their extensive use in Internet-based applications, ontologies have gained significant popularity and recognition within the semantic web domain. They are widely regarded as valuable sources of semantics and interoperability in artificial intelligence systems. With the exponential growth of unstructured data on the web, there is a pressing need for automated acquisition of ontologies from unstructured text. This research area has seen the emergence of various methodologies that leverage techniques from machine learning, text mining, knowledge representation and reasoning, information retrieval, and high level natural language processing. These new techniques represent an opportunity to introduce automation into the process of ontology acquisition from unstructured text. To this end, this contribution offers a semi-automatic framework with a concrete usage of a tooled NLP-based approach to design an application ontology in a real-world industrial context. We discuss the state of the art analysis, the challenges met and the technological choices for the realization of this approach. Specifically, we explore its application in the real-world scenario of RTE's power grid event management.
Domaines
Informatique [cs]
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_SMD__AI_Hybridation_in_a_Dynamic_Environment_for_Ontology_Desig.pdf (774.55 Ko)
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