Preliminary results using Snorocket to detect errors in the post-coordination of SNOMED CT

We present preliminary results for the application of a procedure that detects and corrects errors in concept definitions of a local interface vocabulary with SNOMED CT as its reference vocabulary. Using the relations inferred by SNOROCKET we detected redundant fully defined concepts, but also we de...

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Detalles Bibliográficos
Autores principales: Avila, Pilar, Gambarte, María Laura, Berinsky, Hernán, Benítez, Sonia, Park, Hee, Luna, Daniel, Pérez, David, Campos, Fernando, Zanetti, Sofía, Díaz, Soledad, López, Alejandro
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2016
Materias:
Ciencias Informáticas
Interfaz Usuario-Computador
Vocabulario Controlado
Control de Calidad
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/56532
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-56532
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Interfaz Usuario-Computador
Vocabulario Controlado
Control de Calidad
spellingShingle Ciencias Informáticas
Interfaz Usuario-Computador
Vocabulario Controlado
Control de Calidad
Avila, Pilar
Gambarte, María Laura
Berinsky, Hernán
Benítez, Sonia
Park, Hee
Luna, Daniel
Pérez, David
Campos, Fernando
Zanetti, Sofía
Díaz, Soledad
López, Alejandro
Preliminary results using Snorocket to detect errors in the post-coordination of SNOMED CT
topic_facet Ciencias Informáticas
Interfaz Usuario-Computador
Vocabulario Controlado
Control de Calidad
description We present preliminary results for the application of a procedure that detects and corrects errors in concept definitions of a local interface vocabulary with SNOMED CT as its reference vocabulary. Using the relations inferred by SNOROCKET we detected redundant fully defined concepts, but also we detected suspected patterns where concepts had redundant inferred relations. Our procedure detected errors in 1.63% of the whole vocabulary, the primary type of error was produced by duplications since these concepts did not exist when the knowledge modeler asserted them. Using these results, we implemented a GUI to track patterns and correct errors. Our procedure contributes to the quality assurance of our local interface vocabulary since errors in the hierarchies can compromise interoperability and meaningful use of the vocabulary. Our approach could be used by thesaurus implementers to detect suspected patterns, grouping them, and offer a centralized interface to correct them.
format Objeto de conferencia
Objeto de conferencia
author Avila, Pilar
Gambarte, María Laura
Berinsky, Hernán
Benítez, Sonia
Park, Hee
Luna, Daniel
Pérez, David
Campos, Fernando
Zanetti, Sofía
Díaz, Soledad
López, Alejandro
author_facet Avila, Pilar
Gambarte, María Laura
Berinsky, Hernán
Benítez, Sonia
Park, Hee
Luna, Daniel
Pérez, David
Campos, Fernando
Zanetti, Sofía
Díaz, Soledad
López, Alejandro
author_sort Avila, Pilar
title Preliminary results using Snorocket to detect errors in the post-coordination of SNOMED CT
title_short Preliminary results using Snorocket to detect errors in the post-coordination of SNOMED CT
title_full Preliminary results using Snorocket to detect errors in the post-coordination of SNOMED CT
title_fullStr Preliminary results using Snorocket to detect errors in the post-coordination of SNOMED CT
title_full_unstemmed Preliminary results using Snorocket to detect errors in the post-coordination of SNOMED CT
title_sort preliminary results using snorocket to detect errors in the post-coordination of snomed ct
publishDate 2016
url http://sedici.unlp.edu.ar/handle/10915/56532
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