User Oriented Semi-automatic Method of Constructing Domain Ontology

Qu, Chao; Liu, Fagui; Yu, Hui; Yuan, Ruifen; Wang, Anxiong

doi:10.1007/978-981-10-0356-1_58

Cited by 2 publications

(5 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The ontology development methodology defines the steps and the pathway to design, implement, and verify a domain-specific ontology. This paper refers to and adjusts some mature ontology engineering methods that are already applied in other industrial domains (López et al, 1999; El-Diraby, 2013; Chantrapornchai and Choksuchat, 2016; Kethavarapu and Saraswathi, 2016; Qu et al, 2016). In Steps II and III, a heuristic methodology for defining and integrating ontologies is detailed since they are part of contributions of this paper.…”

Section: Framework and Methodologymentioning

confidence: 99%

Multiple aspects maintenance ontology-based intelligent maintenance optimization framework for safety-critical systems

Diao,

Zhao,

Vaddi

et al. 2024

AIEDAM

View full text Add to dashboard Cite

Maintenance optimization is a process for improving the efficiency of maintenance strategies and activities, considering various aspects of the target system and components, such as the probabilities of system failures and the cost of repair and replacement of a failed component. The improvement of maintenance optimization algorithms generally requires information from various data sources. For example, it may require the system risk information derived from risk analysis tools or the residual lifetime of a component from fault prognosis tools. The requirements of data acquisition (DAQ) and aggregation pose new challenges for maintenance management systems (MMSs) that implement and use these maintenance optimization algorithms. This paper proposes a multiple aspects maintenance ontology-based framework to facilitate DAQ from MMSs, online monitoring systems, fault detection and discrimination tools, risk assessment tools, decision-making tools, and component identification tools, and accelerate the implementation and verification of contemporary maintenance optimization models and algorithms. The proposed framework consists of a multi-aspect maintenance ontology with critical information for maintenance optimization and application interfaces for collecting information from various data sources, such as fault prognosis tools, online monitoring tools, risk assessment tools, and decision-making algorithms. In addition, this paper proposes a heuristic method for integrating concepts and properties from other existing ontologies into the proposed framework when the existing ontology is not fully compatible with the ontology under construction. Finally, the paper verifies the proposed ontology framework using a feedwater system designed for nuclear power plants with valves and filters as the components under maintenance.

show abstract

Section: Framework and Methodologymentioning

confidence: 99%

Multiple aspects maintenance ontology-based intelligent maintenance optimization framework for safety-critical systems

Diao,

Zhao,

Vaddi

et al. 2024

AIEDAM

View full text Add to dashboard Cite

show abstract

“…But to obtain a comprehensive set of features along with the similar SOA, comparative surveys like Fernández-López (1999), Fernández-López and Gómez-Pérez (2002), Corcho et al (2003) and Pinto and Martins (2004) were considered. The other literature that describes ODM approaches like Qu et al (2015), Dutta et al (2015), Suárez-Figueroa et al (2015), Dutta and Sinha (2018) that have come over the years were also used. The features were scattered and distributed in the various research works in different quantities.…”

Section: Odm Ranking Framework (Odmrf)mentioning

confidence: 99%

“…Three ways of designing ontologies (Qu et al, 2015), namely, manual ontology construction process (MOCP), automatic ontology construction process (AOCP) and semiautomatic ontology construction process (SOCP). In MOCP, all tasks of designing ontology are done manually by an OC.…”

Section: Aspects Encompassedmentioning

confidence: 99%

“…The present work analysed these literature to derive the features. The studies used were Aussenac-Gilles et al (2000), Fernández-López (1999), Fernández-López and Gómez-Pérez (2002), Corcho et al (2003), Pinto and Martins (2004), Islam et al (2010), Iqbal et al (2013), Al-Baltah et al (2014), Simperl and Luczak-Rösch (2014), Qu et al (2015), Dutta et al (2015), Suárez-Figueroa et al (2015), Kotis et al (2020), Aminu et al (2020), Sattar et al (2020) and Spoladore and Pessot (2021). The features specified in these peer-reviewed literature are well-defined, well-accepted and are expected to be suitable enough to cover most aspects of ODM.…”

Section: Pilot Study (Ps)mentioning

confidence: 99%

“…),Corcho et al (2003) andPinto and Martins (2004) were considered. The other literature that describes ODM approaches likeQu et al (2015),Dutta et al (2015), Su arez-Figueroa et al…”

mentioning

confidence: 99%

See 2 more Smart Citations

Ranking the ontology development methodologies using the weighted decision matrix

Sinha

Dutta

Varadarajan

2022

DTA

View full text Add to dashboard Cite

PurposeThe current work provides a framework for the ranking of ontology development methodologies (ODMs).Design/methodology/approachThe framework is a step-by-step approach reinforced by an array of ranking features and a quantitative tool, weighted decision matrix. An extensive literature investigation revealed a set of aspects that regulate ODMs. The aspects and existing state-of-the-art estimates facilitated in extracting the features. To determine weight to each of the features, an online survey was implemented to secure evidence from the Semantic Web community. To demonstrate the framework, the authors perform a pilot study, where a collection of domain ODMs, reported in 2000–2019, is used.FindingsState-of-the-art research revealed that ODMs have been accumulated, surveyed and assessed to prescribe the best probable ODM for ontology development. But none of the prevailing studies provide a ranking mechanism for ODMs. The recommended framework overcomes this limitation and gives a systematic and uniform way of ranking the ODMs. The pilot study yielded NeOn as the top-ranked ODM in the recent two decades.Originality/valueThere is no work in the literature that has investigated ranking the ODMs. Hence, this is a first of its kind work in the area of ODM research. The framework supports identifying the topmost ODMs from the literature possessing a substantial amount of features for ontology development. It also enables the selection of the best possible ODM for the ontology development.

show abstract

User Oriented Semi-automatic Method of Constructing Domain Ontology

Cited by 2 publications

References 5 publications

Multiple aspects maintenance ontology-based intelligent maintenance optimization framework for safety-critical systems

Multiple aspects maintenance ontology-based intelligent maintenance optimization framework for safety-critical systems

Ranking the ontology development methodologies using the weighted decision matrix

Contact Info

Product

Resources

About