This presentation provides an overview of knowledge engineering and knowledge-based systems. It defines knowledge engineering as integrating knowledge into computer systems to solve complex problems requiring human expertise. The presentation discusses different views of knowledge engineering, trends in the field like the paradigm shift from transfer to modeling views, and modeling frameworks like CommonKADS. CommonKADS is highlighted as a leading methodology that supports structured knowledge engineering through detailed task and process analysis and developing knowledge systems to support business processes.

1. SCHOOL OF COMPUTER SCIENCE & IT-
DAVV, INDORE
Presentation on
knowledge based engineering
Presented to: Presented by:
Prof. Ugrasen Suman
Aditya Trivedi
M.Tech.-I sem

2. Goal:
The main goal of this presentation is to understand:
 Knowledge
 Knowledge based engineering
 Principles of knowledge engineering
 Views of knowledge engineering
 Trends in Knowledge Engineering
 Frameworks for knowledge based systems
 commanKADS framework
 References

3. What is knowledge?
Plato:-
“justified true belief”
Knowledge is a familiarity with someone or something, which can
include information, facts, descriptions, and/or skills acquired
through experience or education.
 DATA
 INFORMATION
 KNOWLEDGE

4. Knowledge engineering:
Knowledge engineering (KE) was defined in 1983 by Edward
Feigenbaum, and Pamela McCorduck as follows:
KE is an engineering discipline that involves
integrating knowledge into computer systems in order to solve
complex problems normally requiring a high level of human
expertise.

5. Knowledge engineering for Knowledge based
systems:
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
 Acquisition and structuring of the
related information, knowledge and specific preferences (IPK
model)
 Implementation of the structured knowledge into knowledge bases
 Testing and validation of the inserted knowledge
 Integration and maintenance of the system
 Revision and evaluation of the system.

6. Knowledge engineering principles:
 There are different:
◦ types of knowledge each requiring its own approach and technique.
◦ types of experts and expertise, such that methods should be chosen appropriately.
◦ ways of representing knowledge, which can aid the acquisition, validation and re-
use of knowledge.
◦ ways of using knowledge, so that the acquisition process can be guided by the
project aims (goal-oriented).
 Structured methods increase the efficiency of the acquisition
process.
 Knowledge Engineering is the process of eliciting Knowledge for
any purpose be it Expert system or AI development

7. Views of knowledge engineering:
There are two main views to knowledge engineering:
 Transfer View
 Modelling View

8. Overview of Trends in Knowledge Engineering:
 The paradigm Shift from a transfer view to a modelling view
 The evolving of Role Limiting methods and Generic Tasks
 The usage of Modelling Frameworks
 The influence of Ontology

9. Modelling frameworks for knowledge based
systems:
 commonKDAS
 MIKE(Model-based and incremental knowledge Engineering)
 PROTÉGÉ-II

10. What is CommonKADS?
 CommonKADS is the leading methodology to support structured
knowledge engineering.
 enables to spot the opportunities and bottlenecks in how
organizations develop, distribute and apply their knowledge
resources, and so gives tools for corporate knowledge management.
 provides the methods to perform a detailed analysis of knowledge-
intensive tasks and processes.
 supports the development of knowledge systems that support
selected parts of the business process.

11. CommonKADS model suite:

12. References:
 www.wikipedia.org
 www.commonkads.uva.nl
 Book by Schreiber et al “Knowledge
Engineering and Management”
published by University press.

13. Thank you..!!
Queries??