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|Abstract=The paper describes the MIKE (Model-based and Incremental Knowledge Engineering) approach for developing knowledge-based systems. MIKE integrates semiformal and formal specification techniques together with prototyping into a coherent framework. All activities in the building process of a knowledge-based system are embedded in a cyclic process model. For the semiformal representation we use a hypermedia-based formalism which serves as a communication basis between expert and knowledge engineer during knowledge acquisition. The semiformal knowledge representation is also the basis for formalization, resulting in a formal and executable model, specified in the Knowledge Acquisition and Representation Language (KARL). Since KARL is executable the model of expertise can be developed and validated by prototyping. A smooth transition from a semiformal to a formal specification and further on to design is achieved because all the description techniques rely on the same conceptual model to describe the functional and non-functional aspects of the system. Thus, the system is thoroughly documented at different description levels, each of which focuses on a distinct aspect of the entire development effort. Traceability of requirements is supported by linking the different models to each other. | |Abstract=The paper describes the MIKE (Model-based and Incremental Knowledge Engineering) approach for developing knowledge-based systems. MIKE integrates semiformal and formal specification techniques together with prototyping into a coherent framework. All activities in the building process of a knowledge-based system are embedded in a cyclic process model. For the semiformal representation we use a hypermedia-based formalism which serves as a communication basis between expert and knowledge engineer during knowledge acquisition. The semiformal knowledge representation is also the basis for formalization, resulting in a formal and executable model, specified in the Knowledge Acquisition and Representation Language (KARL). Since KARL is executable the model of expertise can be developed and validated by prototyping. A smooth transition from a semiformal to a formal specification and further on to design is achieved because all the description techniques rely on the same conceptual model to describe the functional and non-functional aspects of the system. Thus, the system is thoroughly documented at different description levels, each of which focuses on a distinct aspect of the entire development effort. Traceability of requirements is supported by linking the different models to each other. | ||
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Version vom 7. August 2009, 12:49 Uhr
Developing Knowledge-Based Systems with MIKE
Developing Knowledge-Based Systems with MIKE
Veröffentlicht: 1998 Oktober
Journal: Journal of Automated Software Engineering
Nummer: 4
Seiten: 389-418
Volume: 5
Referierte Veröffentlichung
Kurzfassung
The paper describes the MIKE (Model-based and Incremental Knowledge Engineering) approach for developing knowledge-based systems. MIKE integrates semiformal and formal specification techniques together with prototyping into a coherent framework. All activities in the building process of a knowledge-based system are embedded in a cyclic process model. For the semiformal representation we use a hypermedia-based formalism which serves as a communication basis between expert and knowledge engineer during knowledge acquisition. The semiformal knowledge representation is also the basis for formalization, resulting in a formal and executable model, specified in the Knowledge Acquisition and Representation Language (KARL). Since KARL is executable the model of expertise can be developed and validated by prototyping. A smooth transition from a semiformal to a formal specification and further on to design is achieved because all the description techniques rely on the same conceptual model to describe the functional and non-functional aspects of the system. Thus, the system is thoroughly documented at different description levels, each of which focuses on a distinct aspect of the entire development effort. Traceability of requirements is supported by linking the different models to each other.
Download: Media:1998_552_Angele_Developing Know_1.ps