A SCRIPT-BASED KNOWLEDGE REPRESENTATION FOR INTELLIGENT OFFICE INFORMATION SYSTEMS (AUDITING)
Abstract
Intelligent Office Information Systems integrate problem solving, natural language processing, knowledge representation, information management and other capabilities that are necessary for supporting the various functions of an organization. This research focuses on the problem solving aspect, and attempts to model organizational problem solving behavior, in planning and acting, using script-based knowledge representation techniques. The philosophy of object-oriented programming languages is useful in describing the behavior of the different parts of the organization that coordinate and cooperate in a problem solving situation. Problem solving in office information systems call for facilities for natural language processing for testing the effectivity of the proposed model. Natural language processing is a problem solving activity and theories for representing knowledge in NLP provide the basis for developing a unified theory of representing and using knowledge that is appropriate for intelligent OISs for audit support. The components of the proposed OIS for audit problem solving are based on Discourse Representation Theory, Conceptual Graph Theory, and Scripts. Queries involving direct data retrieval, postcondition and precondition analysis, and deduction are processed in the system.
Degree
Ph.D.
Subject Area
Management
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