Rule-based ontological knowledge base for monitoring partners across supply networks

Chi, Yu‐Liang

doi:10.1016/j.eswa.2009.06.097

Cited by 45 publications

(14 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The extracted concepts were specified as classes, individuals, and relationships between classes and individuals in order to define the obesity management ontology according to the foundational ontology determined in the second phase [18]. The “OBO relationship ontology of the Open Biological and Biomedical Ontologies” (OBO) [19,20] and the linkage concept hierarchy of SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms) were referred to when defining the relationships.…”

Section: Methodsmentioning

confidence: 99%

Development of an Obesity Management Ontology Based on the Nursing Process for the Mobile-Device Domain

Kim¹,

Park²,

Min³

et al. 2013

J Med Internet Res

View full text Add to dashboard Cite

BackgroundLifestyle modification is the most important factor in the management of obesity. It is therefore essential to enhance client participation in voluntary and continuous weight control.ObjectiveThe aim of this study was to develop an obesity management ontology for application in the mobile-device domain. We considered the concepts of client participation in behavioral modification for obesity management and focused on minimizing the amount of information exchange between the application and the database when providing tailored interventions.MethodsAn obesity management ontology was developed in seven phases: (1) defining the scope of obesity management, (2) selecting a foundational ontology, (3) extracting the concepts, (4) assigning relationships between these concepts, (5) evaluating representative layers of ontology content, (6) representing the ontology formally with Protégé, and (7) developing a prototype application for obesity management.ResultsBehavioral interventions, dietary advice, and physical activity were proposed as obesity management strategies. The nursing process was selected as a foundation of ontology, representing the obesity management process. We extracted 127 concepts, which included assessment data (eg, sex, body mass index, and waist circumference), inferred data to represent nursing diagnoses and evaluations (eg, degree of and reason for obesity, and success or failure of lifestyle modifications), and implementation (eg, education and advice). The relationship linking concepts were “part of”, “instance of”, “derives of”, “derives into”, “has plan”, “followed by”, and “has intention”. The concepts and relationships were formally represented using Protégé. The evaluation score of the obesity management ontology was 4.5 out of 5. An Android-based obesity management application comprising both agent and client parts was developed.ConclusionsWe have developed an ontology for representing obesity management with the nursing process as a foundation of ontology.

show abstract

Section: Methodsmentioning

confidence: 99%

Development of an Obesity Management Ontology Based on the Nursing Process for the Mobile-Device Domain

Kim¹,

Park²,

Min³

et al. 2013

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“…CHI proposed a rule-based model for supplier discovery based on an ontology-based description of capabilities. Here, the manufacturing suppliers are mainly characterized through the parts and products they produce and there is no direct reference to the manufacturing processes or resources provided by the suppliers [20].…”

Section: Selection Of Appropriate Resourcesmentioning

confidence: 99%

Ontology-based Determination of Alternative CNC Machines for a Flexible Resource Allocation

Rehage

Gausemeier

2015

Procedia CIRP

View full text Add to dashboard Cite

In case of an unplanned machine breakdown, alternative resources have to be found quickly to avoid delays in following process steps. In order to counter this, an automated determination of alternative CNC-machines and a reliable validation is proposed. First, a rough process description is extracted from the NC program. Second, a suitable machine is searched in an ontology based on the rough process description. The ontology contains a description of all needed properties of a machine and rules to derive the resulting capabilities. Third, the NC program is validated on a virtual machine to ensure the absence of errors.

show abstract

“…Chi proposed a rule-based model for supplier discovery with an underlying ontology-based description of capabilities. The manufacturing suppliers are mainly characterized through the parts and products they produce and there is no direct reference to the manufacturing processes or resources provided by the suppliers [16].…”

Section: Relevant Research Areasmentioning

confidence: 99%

Ontology-Based Finding of Feasible Machine Changes

Rehage

Gausemeier

2015

Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth

View full text Add to dashboard Cite

Abstract. In the event of a machine fault, feasible machine changes have to be reviewed by the operation scheduling and dispatching to avoid remarkable delays. In this approach, this is achieved by an automated identification of alternative machine tools and a reliable validation. First, a capable machine that satisfies the requirements of the NC program is searched within an ontology. Therefore, the ontology contains a description of all relevant characteristics of specific machine tools and expert rules to derive provided capabilities. Second, the NC program is validated on a virtual machine tool to ensure its accuracy.

show abstract

Rule-based ontological knowledge base for monitoring partners across supply networks

Cited by 45 publications

References 12 publications

Development of an Obesity Management Ontology Based on the Nursing Process for the Mobile-Device Domain

Development of an Obesity Management Ontology Based on the Nursing Process for the Mobile-Device Domain

Ontology-based Determination of Alternative CNC Machines for a Flexible Resource Allocation

Ontology-Based Finding of Feasible Machine Changes

Contact Info

Product

Resources

About