<div class="csl-bib-body">
<div class="csl-entry">Breit, A., Waltersdorfer, L., Ekaputra, F. J., Miksa, T., & Sabou, M. (2022). A Lifecycle Framework for Semantic Web Machine Learning Systems. In <i>Database and Expert Systems Applications - DEXA 2022 Workshops</i> (pp. 359–368). https://doi.org/10.1007/978-3-031-14343-4_33</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/190009
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dc.description.abstract
Semantic Web Machine Learning Systems (SWeMLS) characterise applications, which combine symbolic and subsymbolic components in innovative ways. Such hybrid systems are expected to benefit from both domains and reach new performance levels for complex tasks. While existing taxonomies in this field focus on building blocks and patterns for describing the interaction within the final systems, typical lifecycles describing the steps of the entire development process have not yet been introduced. Thus, we present our SWeMLS lifecycle framework, providing a unified view on Semantic Web, Machine Learning, and their interaction in a SWeMLS. We further apply the framework in a case study based on three systems, described in literature. This work should facilitate the understanding, planning, and communication of SWeMLS designs and process views.
en
dc.description.sponsorship
FFG - Österr. Forschungsförderungs- gesellschaft mbH
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dc.language.iso
en
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dc.relation.ispartofseries
Communications in Computer and Information Science
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dc.subject
Lifecycle framework
en
dc.subject
Machine Learning
en
dc.subject
Semantic web
en
dc.title
A Lifecycle Framework for Semantic Web Machine Learning Systems
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.contributor.affiliation
Semantic Web Company, Vienna, Austria
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dc.relation.isbn
978-3-031-14343-4
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dc.description.startpage
359
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dc.description.endpage
368
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dc.relation.grantno
877389
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Database and Expert Systems Applications - DEXA 2022 Workshops
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tuw.container.volume
1633
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tuw.peerreviewed
true
-
tuw.project.title
Ontology-Based ARtificial Intelligence in the Environmental Sector
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tuw.researchTopic.id
I4
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tuw.researchTopic.name
Information Systems Engineering
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E194-04 - Forschungsbereich Data Science
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tuw.publisher.doi
10.1007/978-3-031-14343-4_33
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dc.description.numberOfPages
10
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tuw.author.orcid
0000-0002-4929-7875
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tuw.author.orcid
0000-0001-9301-8418
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tuw.event.name
33rd International Conference: Database and Expert Systems Applications - DEXA 2022 Workshops
en
tuw.event.startdate
22-11-2022
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tuw.event.enddate
24-11-2022
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tuw.event.online
On Site
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tuw.event.type
Event for scientific audience
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tuw.event.country
AT
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tuw.event.presenter
Breit, Anna
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tuw.event.track
Multi Track
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wb.sciencebranch
Informatik
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wb.sciencebranch
Wirtschaftswissenschaften
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
5020
-
wb.sciencebranch.value
90
-
wb.sciencebranch.value
10
-
item.fulltext
no Fulltext
-
item.openairecristype
http://purl.org/coar/resource_type/c_5794
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item.cerifentitytype
Publications
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item.openairetype
conference paper
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item.grantfulltext
none
-
item.languageiso639-1
en
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crisitem.author.dept
Semantic Web Company, Austria
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crisitem.author.dept
E194-04 - Forschungsbereich E-Commerce
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crisitem.author.dept
E194-04 - Forschungsbereich E-Commerce
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crisitem.author.dept
E058-06 - Fachbereich Zentrum für Forschungsdatenmanagement
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crisitem.author.dept
E194-04 - Forschungsbereich E-Commerce
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crisitem.author.orcid
0000-0003-4569-2496
-
crisitem.author.orcid
0000-0002-4929-7875
-
crisitem.author.orcid
0000-0001-9301-8418
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
-
crisitem.author.parentorg
E058 - Forschungs-, Technologie- und Innovationssupport
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
-
crisitem.project.funder
FFG - Österr. Forschungsförderungs- gesellschaft mbH