scholarly journals Modeling Frameworks for Knowledge Engineering Approaches

2022 ◽  
pp. 15-20
Author(s):  
Daniel Ashlock
Keyword(s):  
Knowledge Base ◽  
Transfer Process ◽  
Knowledge Engineering ◽  
Knowledge Based Systems ◽  
Human Knowledge ◽  
Production Rules ◽  
Knowledge Based ◽  
New Ideas ◽  
The Creation ◽  
Applied Knowledge

Human knowledge was regarded as a transfer process into an applied knowledge base in the early 1980s as the creation of a Knowledge-Based Systems (KBS). The premise behind this transfer was that the KBS-required information already existed and only needed to be gathered and applied. Most of the time, the necessary information was gleaned through talking to professionals about how they handle particular problems. This knowledge was usually put to use in production rules, which were then carried out by a rule interpreter linked to them. Here, we demonstrate a number of new ideas and approaches that have emerged during the last few years. This paper presents MIKE, PROTÉGÉ-II, and Common KADS as three different modeling frameworks that may be used together or separately.

Engineering experts critics for cooperative systems

1993 ◽  
Vol 8 (4) ◽  
pp. 309-328 ◽  
Author(s):  
Barry G. Silverman ◽  
R. Gregory Wenig
Keyword(s):  
Knowledge Base ◽  
Traditional Knowledge ◽  
Knowledge Engineering ◽  
Domain Expert ◽  
Human Knowledge ◽  
Cooperative System ◽  
Knowledge Engineer ◽  
Human Expert ◽  
Knowledge Based ◽  
To Come

AbstractKnowledge collection systems often assume they are cooperating with an unbiased expert. They have few functions for checking and fixing the realism of the expertise transferred to the knowledge base, plan, document or other product of the interaction. The same problem arises when human knowledge engineers interview experts. The knowledge engineer may suffer from the same biases as the domain expert. Such biases remain in the knowledge base and cause difficulties for years to come.To prevent such difficulties, this paper introduces the reader to “critic engineering”, a methodology that is useful when it is necessary to doubt, trap and repair expert judgment during a knowledge collection process. With the use of this method, the human expert and knowledge-based critic form a cooperative system. Neither agent alone can complete the task as well as the two together.The methodology suggested here offers a number of extensions to traditional knowledge engineering techniques. Traditional knowledge engineering often answers the questions delineated in generic task (GT) theory, yet GT theory fails to provide four additional sets of questions that one must answer to engineer a knowledge base, plan, design or diagnosis when the expert is prone to error. This extended methodology is called “critic engineering”.

scholarly journals A META-TOOL TO SUPPORT THE DEVELOPMENT OF KNOWLEDGE ENGINEERING METHODOLOGIES AND PROJECTS

2012 ◽  
Vol 22 (08) ◽  
pp. 1055-1083
Author(s):  
JOSÉ ELOY FLÓREZ ◽  
JAVIER CARBÓ ◽  
FERNANDO FERNÁNDEZ
Keyword(s):  
Knowledge Acquisition ◽  
Ad Hoc ◽  
Knowledge Engineering ◽  
Domain Specific ◽  
Advantages And Disadvantages ◽  
Knowledge Based ◽  
Combined Application ◽  
Processing Information ◽  
Knowledge Acquisition Methods ◽  
Applied Knowledge

Knowledge-based systems (KBSs) or expert systems (ESs) are able to solve problems generally through the application of knowledge representing a domain and a set of inference rules. In knowledge engineering (KE), the use of KBSs in the real world, three principal disadvantages have been encountered. First, the knowledge acquisition process has a very high cost in terms of money and time. Second, processing information provided by experts is often difficult and tedious. Third, the establishment of mark times associated with each project phase is difficult due to the complexity described in the previous two points. In response to these obstacles, many methodologies have been developed, most of which include a tool to support the application of the given methodology. Nevertheless, there are advantages and disadvantages inherent in KE methodologies, as well. For instance, particular phases or components of certain methodologies seem to be better equipped than others to respond to a given problem. However, since KE tools currently available support just one methodology the joint use of these phases or components from different methodologies for the solution of a particular problem is hindered. This paper presents KEManager, a generic meta-tool that facilitates the definition and combined application of phases or components from different methodologies. Although other methodologies could be defined and combined in the KEManager, this paper focuses on the combination of two well-known KE methodologies, CommonKADS and IDEAL, together with the most commonly-applied knowledge acquisition methods. The result is an example of the ad hoc creation of a new methodology from pre-existing methodologies, allowing for the adaptation of the KE process to an organization or domain-specific characteristics. The tool was evaluated by students at Carlos III University of Madrid (Spain).

Design and Implementation of an Intelligent CAD System

1987 ◽  
Author(s):  
M. J. Jakiela ◽  
P. Y. Papalambros
Keyword(s):  
Computer Aided Design ◽  
Design System ◽  
Knowledge Based Systems ◽  
Production Rules ◽  
Automated Assembly ◽  
Cad System ◽  
Design And Implementation ◽  
Knowledge Based ◽  
System Requirements ◽  
Aided Design

Abstract System requirements and system design for integrating a production rule program and a computer aided design system are presented. An implementation using a commercially available graphics modeling system is described. A “suggestive mode” interface is programmed as an example with application to design for automated assembly. Initial use of the implementation indicates that encoding production rules is more difficult than with conventional text-only knowledge-based systems, but that this system is a more effective way to use artificial intelligence techniques in design.

OPGEN: A System to Identify and Evaluate Potential Applications of Knowledge Based Systems

1992 ◽  
Author(s):  
Samir Rohatgi ◽  
James H. Oliver ◽  
Stuart S. Chen
Keyword(s):  
Knowledge Acquisition ◽  
Knowledge Base ◽  
Knowledge Based Systems ◽  
The Core ◽  
Knowledge Based ◽  
Evaluation Functions ◽  
Potential Applications ◽  
Computer Based ◽  
Suitable System ◽  
Overall Effectiveness

Abstract This paper describes the development of OPGEN (Opportunity Generator), a computer based system to help identify areas where a knowledge based system (KBS) might be beneficial, and to evaluate whether a suitable system could be developed in that area. The core of the system is a knowledge base used to carry out the identification and evaluation functions. Ancillary functions serve to introduce and demonstrate KBS technology to enhance the overall effectiveness of the system. All aspects of the development, from knowledge acquisition through to testing are presented in this paper.

Evaluation of workbenches which support the CommonKADS methodology

1995 ◽  
Vol 10 (3) ◽  
pp. 269-300 ◽  
Author(s):  
John K. C. Kingston ◽  
Jim G. Doheny ◽  
Ian M. Filby
Keyword(s):  
Knowledge Engineering ◽  
Good Knowledge ◽  
Knowledge Based Systems ◽  
Considerable Effort ◽  
Case Tools ◽  
Knowledge Based ◽  
Specific Support ◽  
Modelling Techniques ◽  
Software Engineers ◽  
Automated Support

AbstractThe KADS methodology and its successor, CommonKADS, have gained a reputation for being useful approaches to building knowledge-based systems in a manner which is both systematic and well documented. However, these methods require considerable effort to use them completely. It has been suggested that automated support for KADS or CommonKADS users, in the form of “knowledge engineering workbenches”, could be very useful. These tools would provide computerised assistance to knowledge engineers in organising and representing knowledge, in a similar fashion to the support which CASE tools provide for software engineers. To provide support for KADS or CommonKADS, the workbenches should provide specific support for the modelling techniques recommended by these methods, which are very detailed in the representation and analysis stages of knowledge engineering. A good knowledge engineering workbench should also be easy to use, should be robust and reliable, and should generate output in a presentable format.This paper reports on an evaluation of two commercially available workbenches for supporting the KADS approach: KADS Tool from ILOG and Open KADS Tool from Bull. This evaluation was carried out by AIAI as part of the CATALYST project, funded by the European Community's ESSI programme, which aimed to introduce CommonKADS to two technology-oriented companies. Information is also presented on two other workbenches: the CommonKADS workbench (which will soon become commercially available) and the VITAL workbench. The results show various strengths and weaknesses in each tool.

Towards Knowledge-Based Spatial Planning

2019 ◽  
pp. 1-15
Author(s):  
Robert Laurini
Keyword(s):  
Big Data ◽  
Spatial Planning ◽  
Knowledge Engineering ◽  
Big Data Analytics ◽  
Human Knowledge ◽  
Collective Knowledge ◽  
Knowledge Based ◽  
Engineering Practices ◽  
Physical Laws

For millennia, spatial planning has been based on human knowledge about the context and its environment together with some objectives of development. Now, with artificial intelligence and especially knowledge engineering, practices of spatial planning can be renovated. Presently, novel practices can be designed. In addition to human collective knowledge, some new chunks of knowledge can be introduced, coming from physical laws, administrative regulations, standards, data mining, and best practices. By big data analytics, some regularities and patterns can be discovered, which again will lead to new actions towards cities: in other words, there is a virtuous circle linking smart territories and big data that can be the basis for novel spatial planning. The role of this chapter will be to analyze those new chunks of knowledge and to explain how human knowledge, possibly coming from different stakeholders, can be harmonized with machine-processable knowledge as to be the basis for territorial intelligence.

Knowledge Extraction from Domain-Specific Documents

2017 ◽  
pp. 106-123
Author(s):  
Ram Kumar ◽  
Shailesh Jaloree ◽  
R. S. Thakur
Keyword(s):  
Knowledge Representation ◽  
Knowledge Base ◽  
Knowledge Bases ◽  
Domain Ontology ◽  
Knowledge Based Systems ◽  
Domain Specific ◽  
Knowledge Based ◽  
Representation Systems ◽  
Terminological Confusion ◽  
Knowledge Representation Systems

Knowledge-based systems have become widespread in modern years. Knowledge-base developers need to be able to share and reuse knowledge bases that they build. As a result, interoperability among different knowledge-representation systems is essential. Domain ontology seeks to reduce conceptual and terminological confusion among users who need to share various kind of information. This paper shows how these structures make it possible to bridge the gap between standard objects and Knowledge-based Systems.

Transferring Knowledge in a Knowledge-Based Economy

2009 ◽  
pp. 862-870 ◽  
Author(s):  
Lauren Edelstein Henry ◽  
Doris Lee
Keyword(s):  
Knowledge Management ◽  
Knowledge Transfer ◽  
Literature Review ◽  
Transfer Process ◽  
Background Information ◽  
Pertinent Literature ◽  
Knowledge Based ◽  
Knowledge Based Economy ◽  
Independent Analysis ◽  
The Creation

Knowledge is considered a major asset for companies competing in today’s knowledge-based economy. Management and retention of this knowledge is a critical task in keeping companies ahead of the game. This article will focus on one component of knowledge management, that is, the creation of a successful knowledge transfer process by using an integrative literature review method (Torracco, 2005). An integrative literature review is a form of research where the pertinent literature on a topic was systematically reviewed, analyzed, and synthesized in hopes of reaching a new and better understanding of the topic. Multiple databases were used in gathering literature for this article. Common themes that serve as findings of the study were through the processes of independent analysis of each researcher and joint discussion of the two researchers of the study. In the following sections, background information and definitions concerning knowledge transfer are presented followed by the identified themes. Finally, pertinent discussions regarding trends of knowledge transfer are discussed.

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