Reasoning-Supported Interactive Revision of Knowledge Bases.

Quality control is an essential task within ontology development projects, especially when the knowledge formalization is partially automatized. We propose a method for integrating newly acquired, possibly low-quality axioms into an existing ontology after their manual inspection; based on the decis...

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Bibliographic Details
Main Authors: Nikitina, N, Rudolph, S, Glimm, B
Other Authors: Walsh, T
Format: Conference item
Published: IJCAI/AAAI 2011
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author Nikitina, N
Rudolph, S
Glimm, B
author2 Walsh, T
author_facet Walsh, T
Nikitina, N
Rudolph, S
Glimm, B
author_sort Nikitina, N
collection OXFORD
description Quality control is an essential task within ontology development projects, especially when the knowledge formalization is partially automatized. We propose a method for integrating newly acquired, possibly low-quality axioms into an existing ontology after their manual inspection; based on the decision whether the axiom is desired or not, several of the yet unevaluated axioms are evaluated automatically. Since the evaluation order can significantly increase the amount of automatization, we further propose the notion of axiom impact. Finally, we introduce decision spaces as structures to efficiently compute the axiom impact and the implicit evaluation decisions. Compared to a naïve implementation, this reduces the number of costly reasoning operations on average by 75%.
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spelling oxford-uuid:3ad9eff3-c1e9-4c45-90ec-7e5cd31e616c2022-03-26T14:04:02ZReasoning-Supported Interactive Revision of Knowledge Bases.Conference itemhttp://purl.org/coar/resource_type/c_5794uuid:3ad9eff3-c1e9-4c45-90ec-7e5cd31e616cSymplectic Elements at OxfordIJCAI/AAAI2011Nikitina, NRudolph, SGlimm, BWalsh, TQuality control is an essential task within ontology development projects, especially when the knowledge formalization is partially automatized. We propose a method for integrating newly acquired, possibly low-quality axioms into an existing ontology after their manual inspection; based on the decision whether the axiom is desired or not, several of the yet unevaluated axioms are evaluated automatically. Since the evaluation order can significantly increase the amount of automatization, we further propose the notion of axiom impact. Finally, we introduce decision spaces as structures to efficiently compute the axiom impact and the implicit evaluation decisions. Compared to a naïve implementation, this reduces the number of costly reasoning operations on average by 75%.
spellingShingle Nikitina, N
Rudolph, S
Glimm, B
Reasoning-Supported Interactive Revision of Knowledge Bases.
title Reasoning-Supported Interactive Revision of Knowledge Bases.
title_full Reasoning-Supported Interactive Revision of Knowledge Bases.
title_fullStr Reasoning-Supported Interactive Revision of Knowledge Bases.
title_full_unstemmed Reasoning-Supported Interactive Revision of Knowledge Bases.
title_short Reasoning-Supported Interactive Revision of Knowledge Bases.
title_sort reasoning supported interactive revision of knowledge bases
work_keys_str_mv AT nikitinan reasoningsupportedinteractiverevisionofknowledgebases
AT rudolphs reasoningsupportedinteractiverevisionofknowledgebases
AT glimmb reasoningsupportedinteractiverevisionofknowledgebases