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

KNOWLEDGE ACQUISITION


THE KNOWLEDGE-ENGINEERING
PROCESS
 Knowledge

acquisition.
 Knowledge representation.
 Knowledge validation.
 Inferencing.
 Explanation and justification.

THE KNOWLEDGE-ENGINEERING PROCESS


SOURCES OF KNOWLEDGE











books,
films,
computer data-bases,
pictures,
maps,
flow diagrams,
stories,

sensors,
radio frequency identification (RFID),
songs

CONT…


identified and collected by machines
(e.g., sensors, scanners,
cameras,pattern matchers, intelligent
agents).

Sources are of knowledge can be divided into
two types: documented knowledge and
undocumented knowledge.

ACQUISITION





Knowledge Acquisition from
Databases
Knowledge Acquisition via the
Internet

LEVELS OF KNOWLEDGE



Shallow Knowledge
 Shallow

knowledge is the
representation of surface-level
information that can be used to deal
with very specific situations




Deep Knowledge
 Deep

knowledge is the internal and
causal structure of a system and involves
the interactions between the system’s
components

MAJOR CATEGORIES OF KNOWLEDGE


Declarative Knowledge




Procedural Knowledge





Declarative knowledge is a descriptive representation of
knowledge

Procedural knowledge considers the manner in which things
work under different sets of circumstances.

Metaknowledge


Metaknowledge is knowledge about knowledge

DIFFICULTIES IN
KNOWLEDGE ACQUISITION
















Experts may not know how to articulate their knowledge or
may be unable to do so.
Experts may lack time or may be unwilling to cooperate.
Testing and refining knowledge is complicated.
Methods for knowledge elicitation may be poorly defined.
System builders tend to collect knowledge from one source,
but the relevant knowledge may be scattered across several
sources.
Builders may attempt to collect documented knowledge rather
than use experts. The knowledge collected may be incomplete.
It is difficult to recognize specific knowledge when it is mixed

up with irrelevant data.
Experts may change their behavior when they are observed or
interviewed.
Problematic interpersonal communication factors may affect
the knowledge engineer and the expert.

REQUIRED SKILLS OF
KNOWLEDGE ENGINEERS
Knowledge engineers are human professionals who are able
to communicate with experts and consolidate knowledge
from various sources to build a valid knowledge base


Computer skills (e.g., hardware, programming,software)



Tolerance and ambivalence




Effective communication abilities (e.g., sensitivity, tact, diplomacy)



Broad educational background



Advanced, socially-sophisticated verbal skills



Fast-learning capabilities (of different domains)



Understanding of organizations and individuals




Wide experience in knowledge engineering



Empathy and patience



Persistence



Logical thinking



Versatility and inventiveness




Self-confidence

ROLES OF KNOWLEDGE ENGINEERS
1.
2.
3.
4.
5.
6.

Advise the expert on the process of interactive
knowledge elicitation.
Set up and appropriately manage the interactive
knowledge acquisition tools.
Edit the unencoded and coded knowledge base
in collaboration with the expert.
Set up and appropriately manage the
knowledge-encoding tools.
Validate application of the knowledge base in

collaboration with the expert.
Train clients in effective use of the knowledge
base in collaboration with the expert by
developing operational and training procedures.
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Cont..