AN INFERENCE BROWSER FOR VERIFYING THE KNOWLEDGE BASE IN KNOWLEDGE-BASED SYSTEMS

1993 ◽  
Vol 02 (03) ◽  
pp. 349-372 ◽  
Author(s):  
SUK I. YOO ◽  
CHANG H. PARK

In developing knowledge-based systems, the process of collecting the knowledge from the experts, representing it in certain formats, and verifying it is required. It is however not easy to verify the formulated knowledge base by checking if a desired conclusion is derived by a sequence of inferring steps. This paper suggests a model of inference browsers by which the knowledge engineers may easily consult a sequence of inferring steps and verify the knowledge base. The suggested inference browser provides the environment in which the knowledge engineers may observe a sequence of inferring steps displayed in the graphical form, access directly the contents of the rules and the facts on the sequence, and observed a newly generated sequence of inferring steps when some of the rules or the facts are changed. Further, based on the graphically displayed inferring sequence, the inference browser itself detects the erroneous inferring step if it exists, analyzes it, and corrects the associated errors in the knowledge base. Finally the suggested inference browser is compared to other similar tools in terms of the facilities they provide.

Author(s):  
Sterling A. Tomellini ◽  
Barry J. Wythoff ◽  
Hugh B. Woodruff

Author(s):  
Samir Rohatgi ◽  
James H. Oliver ◽  
Stuart S. Chen

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.


Author(s):  
Wassim Jaziri ◽  
Faiez Gargouri

Ontologies now play an important role in providing a commonly agreed understanding of a domain and in developing knowledge-based systems. They intend to capture the intrinsic conceptual and semantic structure of a specific domain. Many methodologies, tools and languages are already available to help anthologies’ designers and users. However, a number of questions remain open: what ontology development methodology provides the best guidance to model a given problem, what steps to be performed in order to develop an ontology? which techniques are appropriate for each step? how ontology’ lifecycle steps are upheld by the software tools? how to maintain an ontology and to evolve it in a consistent way? how to adapt an ontology to a given context? To provide answers to these questions, the authors review in this chapter the main methodologies, tools and languages for building, updating and representing ontologies that have been reported in literature.


1992 ◽  
Vol 5 (3) ◽  
pp. 16-32 ◽  
Author(s):  
Youngohc Yoon ◽  
Tor Guimaraes

Author(s):  
Ram Kumar ◽  
Shailesh Jaloree ◽  
R. S. Thakur

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.


1995 ◽  
Vol 10 (1) ◽  
pp. 67-68
Author(s):  
Nicolaas J. I. Mars

A number of groups developing knowledge-based systems have found (or at least posited) that the design and representation of a limitative set of concepts and relations, a so-called ontology, can contribute to sharing and reusing knowledge bases. However, very few descriptions of implemented ontologies have appeared in the literature. No comparison of competing proposals is available, let alone an empirical determination of the benefits of using an ontology. There is no accepted method for designing and building such ontologies, nor is it clear how ontologies can best be evaluated.


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