]> 2012-02-11T04:51:21-05:00 A Multiple-Method Knowledge-Acquisition Shell for the Automatic Generation of Knowledge-Acquisition Tools The use of predefined models of problem-solving methods is receiving considerable attention from researchers in the area of knowledge acquisition. Using these models, developers of knowledge-acquisition tools are able to prescribe the roles in which knowledge is used in completing a given task. A number of method-oriented architectures based on a single problem-solving method have been developed by various research groups. Because the methods are domain-independent, method-oriented architectures are also limited by the fact that knowledge roles that depend on domain-specific considerations cannot be represented using the model of problem solving. In addition, the interface between the knowledge-acquisition tool and the application expert cannot adequately convey the role of each knowledge type in the task model. PROTEGE II is a knowledge-acquisition shell that generates knowledge-acquisition tools automatically without presupposing a specific model of problem-solving. The shell manages a library of mechanisms--procedures of grain size smaller than that of problem-solving methods. Mechanisms can be combined in PROTEGE II to construct problem-solving methods and to define the roles of knowledge that depend on domain considerations. Furthermore, PROTEGE II utilizes the concept of adaptation in interfaces to allow the knowledge engineer to produce interfaces that are task- and domain-specific. In this paper, we present the PROTEGE II shell and examine the components of its architecture. We also demonstrate the use of PROTEGE II with a running example, and discuss the design techniques used to overcome the limitation of method-specific architectures. techreport 1992 A Multiple-Method Knowledge-Acquisition Shell for the Automatic Generation of Knowledge-Acquisition Tools KSL-91-24 1992 A Multiple-Method Knowledge-Acquisition Shell for the Automatic Generation of Knowledge-Acquisition Tools 1992 Year Title YES Process note Number Ksl tr id Knowledge Systems, AI Laboratory Institution Has year Has where published Has title Has publishing details Has identifier Has author Bibtype Angel R. Puerta and John W. Egar and Samson W. Tu and Mark A. Musen Author Abstract KSL Technical Report Publication Technical Report