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Communication Dans Un Congrès Année : 2015

A Lexicon-Grammar Based Methodology for Ontology Population for e-Health Applications

Flora Amato
  • Fonction : Auteur
  • PersonId : 1168356
Aniello De Santo
  • Fonction : Auteur
  • PersonId : 1168357
Vincenzo Moscato
  • Fonction : Auteur
  • PersonId : 1168358
Antonio Picariello
  • Fonction : Auteur
  • PersonId : 1168359
Domenico Serpico
  • Fonction : Auteur
  • PersonId : 1168360
Giancarlo Sperlì
  • Fonction : Auteur
  • PersonId : 1168361

Résumé

Nowadays, the need for well-structured ontologies in the medical domain is rising, especially due to the significant support these ontologies bring to a number of groundbreaking applications, such as intelligent medical diagnosis system and decision-support systems. Indeed, the considerable production of clinical data belonging to restricted subdomains has stressed the need for efficient methodologies to automatically process enormous amounts of unstructured, domain-specific information in order to make use of the knowledge these data provide. In this work, we propose a lexicon-grammar-based method for efficient information extraction and retrieval from unstructured medical records in order to enrich a simple ontology descriptive of such a kind of documents. We describe the NLP methodology for extracting RDF triples from unstructured medical records, and show how an existing ontology built by a domain expert can be populated with the set of triples and then enriched through its linking to external resources.
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Dates et versions

hal-03790507 , version 1 (28-09-2022)

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Citer

Flora Amato, Aniello De Santo, Vincenzo Moscato, Antonio Picariello, Domenico Serpico, et al.. A Lexicon-Grammar Based Methodology for Ontology Population for e-Health Applications. Ninth International Conference on Complex, Intelligent and Software-Intensive Systems (CISIS), Jul 2015, Blumenau, France. pp.521-526, ⟨10.1109/CISIS.2015.76⟩. ⟨hal-03790507⟩

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