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Inference in the SOOKAT object-oriented knowledge acquisition tool

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Abstract

The SOOKAT (structured object-oriented knowledge acquisition tool) knowledge acquisition (KA) tool, supporting the SeSKA (seamless structured knowledge acquisition) methodology, integrates phases of KA through seamless transformations between object-oriented (OO) models.

The integration of constructing a knowledge base (KB) can be extended beyond the KA process by performing inferences in instantiations of models constructed during the KA process.

The models, constructed during the KA process, form a framework for performing inferences in instantiations of the models.

Inferences performed in instantiations of OO models are guided by control objects (CO). Messages are sent between COs and components of the inference structure. A specific CO, possibly using subordinate COs, can be specified for each inference strategy.

There exists a mutual CO for forward and backward chaining that can also be used when reasoning according to protocols. In addition, COs for problem-solving methods (PSMs), such as cover-and-differentiate or propose-and-revise, can be used.

Mechanisms for importing PSMs over the Internet, as well as for generating specific COs for PSMs, are under development.

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  1. Department of Computer Science and Engineering, Helsinki University of Technology, Hauenkalliontie 2B54, 02170, Espoo, Finland

    Päivikki Parpola

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Parpola, P. Inference in the SOOKAT object-oriented knowledge acquisition tool. Knowl Inf Syst 8, 310–329 (2005). https://doi.org/10.1007/s10115-004-0181-6

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