Knowledge Engineering Article Index for
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Knowledge Engineering




Various activities of KE specific for the development of a knowledge-based system:
  • Assessment of the problem

  • Development of a knowledge-based system shell/structure

  • Implementation of the structured knowledge into knowledge-bases

  • Acquisition and structuring of the related information, knowledge and specific preferences

  • Testing and validation of the inserted knowledge

  • Integration and maintenance of the system

  • Revision and evaluation of the system.

  • Being still more art than engineering, KE is not as neat as the above list in practice. The phases overlap, the process might be iterative, and many challenges could appear. Recently, emerges Meta-knowledge engineering as a new formal Systemic approach to the development of an unified knowledge and Intelligence theory.


Knowledge Engineering Principles

Since the mid-1980s, knowledge engineers have developed a number of principles, methods and tools that have considerably improved the process of knowledge acquisition and ordering. Some of the key principles are summarized as follows:

  • Knowledge engineers acknowledge that there are different types of knowledge, and that the right approach and technique should be used for the knowledge required.

  • Knowledge engineers acknowledge that there are different types of experts and expertise, such that methods should be chosen appropriately.

  • Knowledge engineers recognize that there are different ways of representing knowledge, which can aid the acquisition, validation and re-use of knowledge.

  • Knowledge engineers recognize that there are different ways of using knowledge, so that the acquisition process can be guided by the project aims ( Goal-oriented ).

  • Knowledge engineers use structured methods to increase the efficiency of the acquisition process.


Views of Knowledge Engineering

There are two main views to knowledge engineering:
  • Transfer View- This is the traditional view. In this view, the assumption is to apply conventional knowledge engineering techniques to transfer human knowledge into artificial intelligent systems.

  • Modeling View- This is the alternative view. In this view, the knowledge engineer attempts to model the knowledge and problem solving techniques of the domain expert into the artificial intelligent system.


Some methodologies to support the development of knowledge or intelligence-based systems:



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