Interfacing a knowledge-based system to a large database

1989 ◽  
Vol 4 (1) ◽  
pp. 31-51 ◽  
Author(s):  
P. M. D. Gray ◽  
I. G. Archibald ◽  
K. Lunn
Keyword(s):  
Expert System ◽  
Relational Database ◽  
Large Database ◽  
End User ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Product Formulation ◽  
Front End ◽  
Mainframe Computer

AbstractThis paper describes the interfacing problem that arose in a Product Formulation expert system written in LISP that had to be interfaced to data in a relational database running on a separate mainframe computer. It surveys the different forms of coupling that are possible and emphasizes the advantages of tight navigational coupling over the more popular set-based coupling. It describes how Prolog was used to overcome the interfacing problems and to provide a customized front end to an end user, based on a navigational interface. It reviews the techniques of using Prolog and the likely obstacles, together with a look forward to databases using Frames or Objects.

An Advisory Conceptual Design Tool for Mechanical Transmission Systems

1994 ◽  
Author(s):  
C. P. Huang ◽  
F. W. Liou ◽  
J. J. Malyamakkil ◽  
W. F. Lu
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Conceptual Design ◽  
Design Process ◽  
Design Tool ◽  
Mechanical Transmission ◽  
Transmission Systems ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Packaging Machine

Abstract This paper presents an advisory conceptual design tool for mechanical transmission systems. Space consideration was taken into account during the design process. A prototype function tree was built in the form of knowledge-based system to transfer a designer’s idea into a set of mechanical components. An advisory expert system was also developed to help a designer in decision making. As an example, a packaging machine is designed using the developed system.

Research to Safety Evaluation Expert System of Hydraulic Engineering Metal Structures

2011 ◽  
Vol 48-49 ◽  
pp. 994-1001 ◽  
Author(s):  
Guang Ming Yang
Keyword(s):  
Expert System ◽  
Relational Database ◽  
Domain Knowledge ◽  
Safety Evaluation ◽  
Database System ◽  
Base System ◽  
Metal Structures ◽  
Knowledge Based ◽  
Knowledge Base System ◽  
Method Base

Combining the successful applications in AI, in this paper, an expert system is studied and designed for evaluating the safety of hydraulic metal structures, whose goal is compute the reliability of hydraulic metal structures. Applying the techniques of AI, a framework is made up for evaluating the safety of hydraulic metal structures. The framework of knowledge base system is designed and presented with the domain knowledge. Based on the theory of relational database, the conceptual and logical views of database system are designed and analysed. Additionally, method base system is designed. A practical example is given to illustrate the process of using this system. This system has features of practical and advanced and expand.

scholarly journals Fasting Ontology in Pillars of Islam

2018 ◽  
Vol 12 (2) ◽  
pp. 562
Author(s):  
Sara Afiqah Mohd Zailani ◽  
Nurul Aswa Omar ◽  
Aida Mustapha ◽  
Mohd Hisyam Abdul Rahim
Keyword(s):  
Life Cycle ◽  
Expert System ◽  
Search Engine ◽  
Ontology Development ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Instance Search ◽  
The Individual

The development of Fasting Ontology in the Pillars of Islam is presented in this paper and has been built based on reliable sources of Islamic Knowledge. The METHONTOLOGY methodology is used for the ontology development, which include identifying motivation scenarios, creating the competency questions, implementation and evaluation. From the beginning of the development of life cycle, the ontology was appraised from the competency questions and the outcome were clear. Therefore, this ontology can link each concept specifically to the individual verse together with the Tafsir that is related to the topics. The ontology proposed will be part of a larger ontology on Five Pillars of Islam. This development of the ontology is intended to refer to the field of learning for other purpose. For instance, search engine, chatbot, expert system or knowledge-based system.

BRAINDEX: An Interactive, Knowledge-Based System Supporting Brain Death Diagnosis

1990 ◽  
Vol 29 (03) ◽  
pp. 193-199 ◽  
Author(s):  
G. Schwarz ◽  
R. Grims ◽  
E. Rumpl ◽  
G. Rom ◽  
G. Pfurtscheller ◽  
...  
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Natural Language ◽  
Brain Death ◽  
Knowledge Based System ◽  
Forward Chaining ◽  
Brain Death Diagnosis ◽  
Knowledge Based ◽  
Expert System Shell

AbstractBRAINDEX (Brain-Death Expert System) is an interactive, knowledge-based expert system offering support to physicians in decision making concerning brain death. The physician is given the possibility of communicating in almost natural language and, therefore, in terms with which he is familiar. This updated version of the system is implemented on an IBM-PC/AT with the expert system shell PC-PLUS and consists of about 430 rules. The determination of brain death is realized with backward chaining and for the optional coma-scaling a forward-chaining mechanism is used.

Web-Dialogue Management for Insurance Products

2011 ◽  
pp. 298-305
Author(s):  
Suleyman Taner ◽  
Henk Koppelaar
Keyword(s):  
Insurance Companies ◽  
End User ◽  
Dialogue Management ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Insurance Product

The IP.COM concept enables an end-user to compose automatically an insurance product after conducting a dialogue with a knowledge-based system. This reduces the dependencies of insurance companies on both the IT and the actuarial expert. The system is able to adjust the dialogue interactively according to the specific needs of the users and asks for the relevant data needed for the desired product.

Human–computer co-operative risk management systems

1990 ◽  
Vol 4 (3) ◽  
pp. 139-150
Author(s):  
Kiyoshi Niwa
Keyword(s):  
Risk Management ◽  
Expert System ◽  
Computer System ◽  
Operative Risk ◽  
Management Systems ◽  
Next Generation ◽  
Project Risk ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Project Risks

This paper presents a new concept, a ‘human-computer co-operative system’, as the next-generation knowledge-based system for application to project risk management. It first discusses the characteristics of project risks followed by the development of a common expert system for managing such risks. Then, system limitations are identified in terms of knowledge association, and a ‘human–computer co-operative system’ is proposed to overcome these limitations by explicitly incorporating human intuitive ability into the computer system. Finally, evaluations of the human–computer co-operative system are also described.

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