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5. KNOWLEDGE ACQUISITION METHODOLOGY

McGraw and Harbison-Briggs (1989) pointed out that the lack of structure and organization of knowledge acquisition is one of the impediments to effective knowledge acquisition. It therefore is essential to establish detailed plans for conducting knowledge acquisition sessions. A knowledge acquisition methodology serves as a guide to knowledge engineers in developing these plans. A methodology established to perform the knowledge acquisition task is comprised of four phases: planning for knowledge acquisition, knowledge extraction, knowledge analysis, and knowledge verification. Table 1 summarizes the steps in each phase.


TABLE 1
A Knowledge Acquisition Methodology
 
Phase Steps
Planning Understand the domain
  Identify domain experts and users
  Define the problem scope
  Identify the type of application
  Develop process models
  Plan KA sessions
Extraction Explain KA approach
  Discuss objectives of KA sessions
  Conduct KA sessions
  Debrief experts
Analysis Analyze KA session outputs
  Transfer knowledge into representations
Verification Develop test scenarios
  Verify knowledge with experts

Knowledge Acquisition Planning. The goal of planning, the most important phase of the knowledge acquisition task, is to understand the problem domain, define the problem scope, and identify experts in the problem domain, analyze various knowledge acquisition techniques, and design proper procedures to acquire knowledge. By discussing with experts, the knowledge engineer can identify the characteristics of the problem and comprehend the kind of knowledge required. Knowledge engineers develop proper group process models to acquire knowledge. Existing group support tools are analyzed so that they can be properly employed in the group process. Major steps in this phase include understanding the domain, identifying experts, defining the problem scope, identifying the type of application, analyzing characteristics of the problem, analyzing characteristics of tools and techniques, developing process models, and planning for knowledge acquisition sessions.

Knowledge Extraction. The primary activity of the knowledge extraction phase is to acquire knowledge from experts through a series of knowledge acquisition sessions in a collaborative environment as described. Each session has its own objective; therefore, knowledge engineers may apply different tools to support the knowledge acquisition techniques used. During each session, knowledge engineers must explain the session objective, the process and approach to acquiring knowledge, and the expected results. Functionalities of tools, procedures of using them, and the techniques employed are explained to the session participants. Outputs from this phase include heuristic, concepts, or classification structures. These may be captured in an electronic format and require further analysis to be represented in particular schemes.

Knowledge Analysis. The primary task of this phase is to analyze outputs from knowledge extraction sessions. Some of the tools may be used to support analysis activities such as identifying a list of key concepts from the brainstorming results. Heuristic, concepts or classification structures are analyzed and formalized into representations that may be in the form of heuristic rules, frames, objects and relations, semantic networks, and classification schemes. These representations are then transformed into specific representation schemes that are supported by an expert system building tool. This transformation is part of an effort to implement a prototype expert system. This prototype system will be used in the knowledge verification phase.

Knowledge Verification. This phase places emphasis on verifying heuristic, concepts, and classification structures with experts. Formalized representations are presented to the experts. A demonstration of the prototype system to users and experts is also useful. In addition, the validation of knowledge acquisition involves identifying the entities to be measured, the types of evidence to be collected, the criteria to be applied, and the type of comparisons to be made to assess validity. Refinements of represented knowledge can be performed by reexamining acquired knowledge in the analysis phase. If the knowledge base is incomplete, additional knowledge acquisition sessions must be conducted to elicit required knowledge. If knowledge captured in the prototype system does not provide solutions to problems, redesign of the knowledge acquisition sessions may require rethinking of the knowledge acquisition approach as well as procedures and techniques employed. A demonstration of the prototype system to users and experts is also useful. Once the prototype expert system has been approved by the experts, knowledge engineers can continue the development effort by fine-tuning the knowledge representation and user interface. By making the verification of the knowledge base a part of the ongoing knowledge acquisition and review process, expert system developers can minimize the time and money wasted and prevent the development of an inappropriate or useless system.


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