1999
DOI: 10.1142/s021819409900019x
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Reusable Knowledge-Based Components for Building Software Applications: A Knowledge Modelling Approach

Abstract: Abstract.In computer science, different types of reusable components for building software applications were proposed as a direct consequence of the emergence of new software programming paradigms. The success of these components for building applications depends on factors such as the flexibility in their combination or the facility for their selection in centralised or distributed environments such as internet.In this article, we propose a general type of reusable component, called primitive of representatio… Show more

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Cited by 5 publications
(2 citation statements)
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“…In order to decouple the functional features of a service from its internal specification, we propose to apply PSM [2] for modeling SGS. A PSM is defined as a domainindependent and knowledge-level specification of a problem solving behavior [2]. Our ontology for the description of PSM is based on the Unified Problem-solving Method Language (UPML) [3].…”
Section: Psm Ontologymentioning
confidence: 99%
“…In order to decouple the functional features of a service from its internal specification, we propose to apply PSM [2] for modeling SGS. A PSM is defined as a domainindependent and knowledge-level specification of a problem solving behavior [2]. Our ontology for the description of PSM is based on the Unified Problem-solving Method Language (UPML) [3].…”
Section: Psm Ontologymentioning
confidence: 99%
“…The particular software implementation requires to associate a particular symbolic representation and inference procedure for each knowledge base and to establish the corresponding control mechanisms for the execution of the global model. For this purpose, advanced knowledge engineering tools can be used such as the KSM environment [7], [8]. For example, the knowledge about relations between customer-needs and components, and the knowledge about assembly constraints can be formulated by a particular frame-based representation ( figure 3) with a special matching inference procedure.…”
Section: Introductionmentioning
confidence: 99%