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  4. Enabling Knowledge Management in Complex Industrial Processes Using Semantic Web Technology
 
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Enabling Knowledge Management in Complex Industrial Processes Using Semantic Web Technology

ISSN
978‐999‐54182‐0‐6
Type
book section
Date Issued
2019-07-03
Author(s)
Milenkovic, Katarina
Mayer, Simon  orcid-logo
Diwold, Konrad
Zehetner, Josef
Abstract
Complex industrial processes produce a multitude of information during the product/service lifecycle. Those data are often stored, but rarely used in the context of
overall process optimization, due to their unstructured format and the inability to integrate them with stored formal knowledge about the domain. This paper proposes a way to mitigate this problem, by extending the standard SPARQL query language to enable the integration of formal knowledge and unstructured data, as well as their joint processing. The paper constitutes an initial definition of the proposed SPARQL extension and demonstrates its applicability in the context of selected examples.
Language
English
HSG Classification
contribution to scientific community
Book title
Proceedings of the 2019 International Conference on Theory and Applications in the Knowledge Economy
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/98451
Subject(s)

computer science

Division(s)

ICS - Institute of Co...

Eprints ID
257265
File(s)
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Thumbnail Image

open.access

Name

TAKE_2019_full_paper.pdf

Size

339.04 KB

Format

Adobe PDF

Checksum (MD5)

a720acff512fecd557b9e4ab0f8e66a5

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