Metaproperty-guided deletion from the instance-level of a knowledge base
Metaproperty-guided deletion from the instance-level of a knowledge base
The ontology modeling practice of engineering metaproperties of concepts is a well-known technique. Some metaproperties of concepts describe the dynamics of concept instances, i.e. how instances can and cannot be altered. We investigate how deletions in an ontology-based knowledge base interact with the metaproperties rigidity and dependence. A particularly useful effect are delete cascades. We evaluate how rigidity and dependence may guide delete cascades in an engineering application. A case study in the area of product development shows that beyond explicitly defined deletions, our approach achieves further automated and desirable deletions of facts with high precision and good recall.
Schon, Claudia
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Staab, Steffen
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Kügler, Patricia
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Schleich, Benjamin
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Wartzack, Sandro
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Schon, Claudia
168b14b3-9af6-4578-b264-7100764f3ea8
Staab, Steffen
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Kügler, Patricia
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Schleich, Benjamin
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Wartzack, Sandro
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Schon, Claudia, Staab, Steffen, Kügler, Patricia, Schleich, Benjamin and Wartzack, Sandro
(2018)
Metaproperty-guided deletion from the instance-level of a knowledge base.
In Knowledge Engineering and Knowledge Management. EKAW 2018.
Springer..
(doi:10.1007/978-3-030-03667-6_26).
Record type:
Conference or Workshop Item
(Paper)
Abstract
The ontology modeling practice of engineering metaproperties of concepts is a well-known technique. Some metaproperties of concepts describe the dynamics of concept instances, i.e. how instances can and cannot be altered. We investigate how deletions in an ontology-based knowledge base interact with the metaproperties rigidity and dependence. A particularly useful effect are delete cascades. We evaluate how rigidity and dependence may guide delete cascades in an engineering application. A case study in the area of product development shows that beyond explicitly defined deletions, our approach achieves further automated and desirable deletions of facts with high precision and good recall.
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Accepted/In Press date: 31 August 2018
e-pub ahead of print date: 31 October 2018
Venue - Dates:
21st International Conference on Knowledge Engineering and Knowledge Management, , Nancy, France, 2018-11-12 - 2018-11-16
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Local EPrints ID: 423221
URI: http://eprints.soton.ac.uk/id/eprint/423221
PURE UUID: b3d76876-defd-4e13-b7f6-0f94e2ceced0
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Date deposited: 19 Sep 2018 16:30
Last modified: 16 Mar 2024 04:22
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Contributors
Author:
Claudia Schon
Author:
Steffen Staab
Author:
Patricia Kügler
Author:
Benjamin Schleich
Author:
Sandro Wartzack
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