1. Expert System Dr. Khoerul Anwar, S.T.,M.T STMIK Pradnya Paramita
alqhoir(at)stimata.ac.id
(c) 2017

2. KNOWLEDGE MODELING METHODS
Manual methods (iterview )
structured,
semistructured,
unstructured
Semiautomatic methods
intended to support the experts by allowing them to build knowledge bases with little or no help from knowledge engineer
intended to help knowledge engineers by allowing them to execute the necessary tasks in a more efficient or effective manner
Automatic methods
the expert and the knowledge engineer are minimized or even eliminated

3. Unstructured interviews

4. structured interviews
A structured interview is a systematic, goal- oriented process.
Organized communication between the knowledge engineer and the expert.

5. Cont…
The knowledge engineer studies available material on the domain to identify major demarcations of the relevant knowledge.
The knowledge engineer reviews the planned ES capabilities. He or she identifies targets for the questions to be asked during the knowledge acquisition session.
The knowledge engineer formally schedules and plans the structured interviews (using a form). Planning includes attending to physical arrangements, defining knowledge acquisition session goals and agendas, and identifying or refining major areas of questioning.
The knowledge engineer may write sample questions, focusing on question type, level, and questioning techniques.
The knowledge engineer ensures that the domain expert understands the purpose and goals of the session and encourages the expert to prepare before the interview.
During the interview, the knowledge engineer follows guidelines for conducting interviews.
During the interview, the knowledge engineer uses directional control to retain the interview’s structure.

6. Other Manual Knowledge Modeling Methods
Case analysis
Critical incident analysis.
Discussions with users.
Commentaries.
Conceptual graphs and models.
Brainstorming.
Prototyping
Multidimensional scaling.
Johnson’s hierarchical clustering.
Performance review

7. Automatic Knowledge Modeling Methods
The process of using computers to extract knowledge from data is called knowledge discovery.
There are two major reasons for the use of automated knowledge acquisition
Good knowledge engineers are highly paid and difficult to find, and
domain experts are usually busy and sometimes uncooperative.

8. Cont..
manual and even semiautomatic elicitation methods are slow and expensive (deficiencies)
The correlation between verbal reports and mental behavior is often weak.
In certain situations, experts are unable to provide an overall account of how they make decisions.
The quality of the system depends too much on the quality of the expert and the knowledge engineer.
The expert does not understand the ES technology.
The knowledge engineer may not understand the business problem.
It is difficult to validate the acquired knowledge.

9. Cont…
Roiger and Geatz (2003), typical methods for knowledge discovery include the following:
Inductive learning.
Neural computing
Genetic algorithms.

10. Contoh Knowledge -> Lele (Arga, …)