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Related Experiment Videos

The project ARIANE: conceptual queries to information databases

M Joubert1, J J Robert, F Miton

  • 1CERTIM. Faculté Médecine, Marseille, France.

Proceedings : a Conference of the American Medical Informatics Association. AMIA Fall Symposium
|January 1, 1996
PubMed
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This study presents conceptual and computational models for information retrieval from large databases. These models, utilizing UMLS knowledge sources, were tested on patient and bibliographic data.

Area of Science:

  • Computer Science
  • Information Science
  • Medical Informatics

Background:

  • Information retrieval systems rely on effective data indexing and querying.
  • Conceptual and computational models are crucial for managing large data collections.
  • Previous work established conceptual graphs and computational models for information retrieval.

Purpose of the Study:

  • To present conceptual and computational models for information retrieval.
  • To demonstrate the application of these models using UMLS knowledge sources.
  • To evaluate the models' performance in querying diverse databases.

Main Methods:

  • Design of a conceptual model using conceptual graphs formalism.
  • Implementation of a computational model for information retrieval.

Related Experiment Videos

  • Testing the models on a patient database and a bibliographical database.

    • Main Results:

    • The conceptual and computational models are effective for information retrieval.
    • UMLS knowledge sources facilitate robust information retrieval.
    • Successful querying demonstrated across patient and bibliographical datasets.

    Conclusions:

    • The developed models provide a viable approach for information retrieval in large databases.
    • Integration with UMLS knowledge sources enhances retrieval capabilities.
    • Further testing confirmed the models' applicability to specialized databases.