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  4. Answering controlled natural language questions over RDF clinical data
 
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2020
Conference Paper
Title

Answering controlled natural language questions over RDF clinical data

Abstract
Clinical trial data requires a lot of processing before it can be submitted in accordance with its standardization requirements. After its processing, data has to be stored carefully, often in different systems and formats. Integrating this data without information loss and enabling easy retrieval for later analysis is a highly challenging task. In this demo, we present our system for answering controlled Natural Language questions over RDF clinical data. Questions entered by a user through the proposed interface are annotated on the fly and suggestions are displayed based on an ontology driven auto-completion system. This approach assures a high level of usability and readability while preserving semantic correctness and accuracy of entered questions.
Author(s)
Karam, Naouel  
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Streibel, Olga
Bayer AG, Berlin
Karjauv, Aray
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Coskun, Goekhan
Bayer AG, Berlin
Paschke, Adrian  
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Mainwork
The Semantic Web. ESWC 2020 Satellite Events. Revised Selected Papers  
Project(s)
Qurator
Funder
Bundesministerium für Bildung und Forschung BMBF (Deutschland)  
Conference
Extended Semantic Web Conference (ESWC) 2020  
File(s)
Download (274.98 KB)
DOI
10.1007/978-3-030-62327-2_22
10.24406/publica-r-409223
Language
English
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Keyword(s)
  • question answering

  • Controlled Natural Language

  • clinical study ontology

  • RDF knowledge base

  • clinical data

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