EXPERT SUPPORT SYSTEMS: INTEGRATING AI TECHNOLOGIES.

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Bibliographic Details
Title:	EXPERT SUPPORT SYSTEMS: INTEGRATING AI TECHNOLOGIES.
Authors:	El-Nnajdawi, M. K.¹ elnajdaw@usic.vill.edu, Stylianou, Athony C.² astylian@unccvm.uncc.edu
Source:	Communications of the ACM. Dec1993, Vol. 36 Issue 12, p55-103. 12p.
Subjects:	Expert systems, Communication & technology, Artificial intelligence, Decision support systems, Management information systems, Problem solving
Abstract:	This article examines the distinguishing characteristics of DSS and ES. We compared the two technologies across a number of dimensions and developed a comprehensive taxonomy of their differences. With these differences in mind, we presented a new model of DSS-ES integration. This new model of integration uses the technical strengths of DSS and ES, combines their approaches to problem solving and decision support, and minimizes the shortcomings from the independent use of each one of them. In addition, it employs other Al-based technologies such as a natural language interface, rule induction, neural networks, and intelligent agents. Concepts and techniques addressed in the literature relating to active DSS, expert critic systems, and case-based reasoning are also incorporated. Consequently, the proposed system gives the user the benefits of already existing forms of integration and eliminates some of their problems and limitations. Decision support systems and ES are important technologies in the IS toolkit. Each one has been, and still can be, applied successfully to many problems in a wide variety of domains.
Database:	Engineering Source

Description
Abstract:	This article examines the distinguishing characteristics of DSS and ES. We compared the two technologies across a number of dimensions and developed a comprehensive taxonomy of their differences. With these differences in mind, we presented a new model of DSS-ES integration. This new model of integration uses the technical strengths of DSS and ES, combines their approaches to problem solving and decision support, and minimizes the shortcomings from the independent use of each one of them. In addition, it employs other Al-based technologies such as a natural language interface, rule induction, neural networks, and intelligent agents. Concepts and techniques addressed in the literature relating to active DSS, expert critic systems, and case-based reasoning are also incorporated. Consequently, the proposed system gives the user the benefits of already existing forms of integration and eliminates some of their problems and limitations. Decision support systems and ES are important technologies in the IS toolkit. Each one has been, and still can be, applied successfully to many problems in a wide variety of domains.
ISSN:	00010782