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Short Communication: S-Trans: Semantic transformation of XML healthcare data into OWL ontology

Authors:

Pham Thi Thu Thuy,

Sungyoung LeeAuthors Info & Claims

Knowledge-Based Systems, Volume 35

Pages 349 - 356

https://doi.org/10.1016/j.knosys.2012.04.009

Published: 01 November 2012 Publication History

Abstract

Most healthcare data are available in XML format, which mainly focuses on the structure level and lacks support for data representation. Therefore, a variety of medical applications and medical semantic search engines have difficulty understanding and integrating healthcare data in a highly heterogeneous environment. OWL (Web Ontology Language) and Semantic Web technologies provide an infrastructure that can solve these problems. The aim of our study is to present a mechanism to ease the interpretation and automate the semantic transformation of XML healthcare data into the OWL ontology (S-Trans), which allows an easier and better semantic communication among hospital information systems. On the basis of the XML schemas (XSD or DTD), we extract the document structure and add more descriptions for XML elements. Moreover, to classify the semantic level of duplicate elements in an XML schema, we propose novel metrics to measure the similarity between them. Experimental results show that the proposed method reliably predicts semantic similarity of duplicates and produces a better-quality OWL ontology.

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Cited By

Zhao BZhang RBai K(2024)A Fuzzy Multigranularity Convolutional Neural Network With Double Attention Mechanisms for Measuring Semantic Textual SimilarityIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.342780132:10(5762-5776)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1109/TFUZZ.2024.3427801
Szczepaniuk HSzczepaniuk E(2023)Cryptographic evidence-based cybersecurity for smart healthcare systemsInformation Sciences: an International Journal10.1016/j.ins.2023.119633649:COnline publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1016/j.ins.2023.119633
Jayabalan MO'daniel T(2016)Access control and privilege management in electronic health recordJournal of Medical Systems10.1007/s10916-016-0589-z40:12(1-9)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1007/s10916-016-0589-z
Show More Cited By

Short Communication: S-Trans: Semantic transformation of XML healthcare data into OWL ontology
1. Applied computing
  1. Document management and text processing

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Published In

cover image Knowledge-Based Systems

Knowledge-Based Systems Volume 35, Issue

November, 2012

375 pages

ISSN:0950-7051

Issue’s Table of Contents

Copyright © © 2012.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 November 2012

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Cited By

Zhao BZhang RBai K(2024)A Fuzzy Multigranularity Convolutional Neural Network With Double Attention Mechanisms for Measuring Semantic Textual SimilarityIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.342780132:10(5762-5776)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1109/TFUZZ.2024.3427801
Szczepaniuk HSzczepaniuk E(2023)Cryptographic evidence-based cybersecurity for smart healthcare systemsInformation Sciences: an International Journal10.1016/j.ins.2023.119633649:COnline publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1016/j.ins.2023.119633
Jayabalan MO'daniel T(2016)Access control and privilege management in electronic health recordJournal of Medical Systems10.1007/s10916-016-0589-z40:12(1-9)Online publication date: 1-Dec-2016
https://dl.acm.org/doi/10.1007/s10916-016-0589-z
Szymczak MZadrożny SBronselaer ADe Tré G(2015)Coreference detection in an XML schemaInformation Sciences: an International Journal10.1016/j.ins.2014.11.002296:C(237-262)Online publication date: 1-Mar-2015
https://dl.acm.org/doi/10.1016/j.ins.2014.11.002
Ma YLu KZhang YJin B(2013)Measuring ontology information by rules based transformationKnowledge-Based Systems10.5555/2770959.277105350:C(234-245)Online publication date: 1-Sep-2013
https://dl.acm.org/doi/10.5555/2770959.2771053

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