1. KNOWLEDGE ACQUISITION
CHAPTER 3
KNOWLEDGE ACQUISITION
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2. Introduction
In knowledge acquisition, mathematics and computer science, graph theory is the study of graphs, mathematical structures used to model pair wise relations between objects. It can be used in the process of knowledge acquisition.
A "graph" in this context refers to a collection of vertices and a collection of edges that connect pairs of vertices
A graph may be undirected, meaning that there is no distinction between the two vertices associated with each edge, or its edges may be directed from one vertex to another
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3. TASKS IN KNOWLEDGE ACQUISITION
Knowledge Acquisition involves getting information from an human expert in a particular area, then put the information into a computer and build a expert system with this information, making the information more clearer and available for the expert to use.
In order to carry out any job you will need some kind of equipment, so in the knowledge acquisition activity, the expert system developer uses tools and aids.
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4. PREREQUISITES FOR ACQUISITION
Companies could employ knowledge mapping method with staff members as part of a staff development program. This would be particularly valuable if the personal map had the same spatial structure as the section knowledge map.
Managers would be able to identify key individuals and plan appropriate and efficient training programs.
Inefficient scheme is often because there is not enough care taken to ensure that all trainees (students) have the necessary prerequisite knowledge to benefit fully from the acquisition.
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5. THE METHODS OF KNOWLEDGE ACQUISITION
The methods of knowledge acquisition can
be divided into manual, semi-automated, and
automated.
The primary manual approach of knowledge
acquisition is interviewing.
The reasoning process of experts can be
tracked by several methods. Protocol analysis
is the primary method used in AI.
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6. CHOOSING THE RIGHT HUMAN EXPERT
A computer which exhibits knowledge relating to gravitational attraction will be expected to calculate force, to know what if any parameters are required in order to calculate force and provide simple explanations.
A human could also do this given the formulae and instruction on how to use it and some answers to specific questions. However a human who can be said to understand gravitational attraction will have a clear understanding of the concepts.
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7. CHOOSING THE RIGHT HUMAN EXPERT
That human would also understand other concepts that are the prerequisites of mass and force.
Therefore, the human expert is much more likely to be able to answer novel questions about gravitational attraction and also see gravitational attraction in new and interesting situations.
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8. INTERVIEWING METHODS Interviewing methods range from completely
unstructured to highly structured.
Repertory Grid Analysis (RGA) is the most
common technique for semi-automated
interviews used in AI.
Several software packages that use RGA
improve the knowledge acquisition process.
Face-to-face interview analysis is the most
commonly used form and it involves a direct
dialog between the expert and knowledge
engineer.
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9. PROBLEMS WITH INTERVIEWING
Unstructured interviewing, according to
McGraw & Harbison-Briggs, seldom
provides complete or well-organized
descriptions of cognitive processes.
This is because the domains are generally
complex ; the expert usually find it very
difficult to express some of the more
important elements of their knowledge ;
domain experts may interpret the lack of
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10. PROBLEMS WITH INTERVIEWING (cont…)
of structure ; data acquired from unstructured
interview are often unrelated, exist in varying levels of complexity, and are difficult for the
knowledge engineer to interpret, and integrate.
For walk-through interview method, it can
be a tedious process. It places great
demands on the domain expert, who must
be able not only to demonstrate expertise
but also to express it.
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11. KNOWLEDGE ANALYSIS Knowledge acquisition and analysis is not
an easy task. It includes identifying the
knowledge, representing the knowledge in
a proper format, structuring the knowledge,
and transferring the knowledge to machine.
This process can be greatly influenced by
the roles of three major participants : the
knowledge engineer, the expert, and the
end-user.
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12. STRUCTURING THE KNOWLEDGE GRAPHICALLY
The graphs studied in graph theory should not be confused with "graphs of functions" and other kinds of graphs
A pictorial representation of a graph
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