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An ontology knowledge inspection methodology for quality assessment and continuous improvement
- Source :
- Investigo. Repositorio Institucional de la Universidade de Vigo, Universidade de Vigo (UVigo)
- Publication Year :
- 2021
- Publisher :
- Elsevier BV, 2021.
-
Abstract
- Ontology-learning methods were introduced in the knowledge engineering area to automatically build ontologies from natural language texts related to a domain. Despite the initial appeal of these methods, automatically generated ontologies may have errors, inconsistencies, and a poor design quality, all of which must be manually fixed, in order to maintain the validity and usefulness of automated output. In this work, we propose a methodology to assess ontologies quality (quantitatively and graphically) and to fix ontology inconsistencies minimizing design defects. The proposed methodology is based on the Deming cycle and is grounded on quality standards that proved effective in the software engineering domain and present high potential to be extended to knowledge engineering quality management. This paper demonstrates that software engineering quality assessment approaches and techniques can be successfully extended and applied to the ontology-fixing and quality improvement problem. The proposed methodology was validated in a testing ontology, by ontology design quality comparison between a manually created and automatically generated ontology. Financiado para publicación en acceso aberto: Universidade de Vigo/CISUG Xunta de Galicia | Ref. ED481B 2017/018 Xunta de Galicia | Ref. ED431C2018 / 55-GRC Ministerio de Economía, Industria y Competitividad | Ref. TIN2017-84658-C2-1-R
- Subjects :
- Ontology quality measures
1203.11 Logicales de Ordenadores
Information Systems and Management
Quality management
Computer science
media_common.quotation_subject
3304.99 Otras
Knowledge engineering
Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática [Domínio/Área Científica]
02 engineering and technology
Ontology (information science)
Domain (software engineering)
Ontology improvement methodology
0202 electrical engineering, electronic engineering, information engineering
1203.17 Informática
Quality (business)
media_common
Ontology
business.industry
Quality assessment
Ciências Naturais::Ciências da Computação e da Informação [Domínio/Área Científica]
020207 software engineering
Ontology fixing
1203.04 Inteligencia Artificial
Deming cycle
020201 artificial intelligence & image processing
Software engineering
business
PDCA
Natural language
Subjects
Details
- ISSN :
- 0169023X
- Volume :
- 133
- Database :
- OpenAIRE
- Journal :
- Data & Knowledge Engineering
- Accession number :
- edsair.doi.dedup.....fd89cc0c577fcffcc842047c561518db
- Full Text :
- https://doi.org/10.1016/j.datak.2021.101889