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Towards Automatic Ontology Alignmentfor Enriching Sensor Data Analysis
Örebro University, School of Science and Technology. (AASS)
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-3122-693X
2013 (English)In: Communications in Computer and Information Science, ISSN 1865-0929, E-ISSN 1865-0937, Vol. 415, 179-193 p.Article in journal (Refereed) Published
Abstract [en]

In this work ontology alignment is used to align an ontology comprising high level knowledge to a structure representing the results of low-level sensor data classification. To resolve inherent uncertainties from the data driven classifier, an ontology about application domain is aligned to the classifier output and the result is recommendation system able to suggest a course of action that will resolve the uncertainty. This work is instantiated in a medical application domain where signals from an electronic nose are classified into different bacteria types. In case of misclassifications resulting from the data driven classifier, the alignment to an ontology representing traditional microbiology tests suggests a subset of tests most relevant to use. The result is a hybrid classification system (electronic nose and traditional testing) that automatically exploits domain knowledge in the identification process.

Place, publisher, year, edition, pages
Springer Berlin Heidelberg, 2013. Vol. 415, 179-193 p.
Keyword [en]
Ontology Alignment, Sensor Data, Classification, Semantic Gap
National Category
Computer Systems Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-34333DOI: 10.1007/978-3-642-54105-6_12Scopus ID: 2-s2.0-84904291206ISBN: 978-3-642-54104-9 (print)OAI: oai:DiVA.org:oru-34333DiVA: diva2:705193
Note

This publication source is also registered as a book w. online ISBN 978-3-642-54105-6 and print ISBN 978-3-642-54104-9. The book series is titled "Communications in Computer and Information Science"

Available from: 2014-03-14 Created: 2014-03-14 Last updated: 2017-10-03Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf