Trace -Based Model in Knowledge Acquisition System for Valuing Knowledge

Abstract

Aims: This paper presents a trace-based model in Knowledge Acquisition System for Valuing Knowledge. In Case Based Reasoning (CBR), solving problems is based on the solutions of similar past problems. From the system’s point of view, this might be true, but from the user’s point of view, identical problems may need different solutions. This is due to that (CBR) suffers from the “frame problem”: in some situations, the context information is missing. Moving from the Case-Based Reasoning to Trace-Based Reasoning (TBR) is the solution of this problem. Trace-Based Reasoning is an extension of the Case-Based Reasoning, allowing the context to be included in the reasoning. Study Design: The model includes three related stages in solving problems; the first is context – aware retrieved information stage and the second is tracing the user tasks in order to cover all the needed elements in the environment of the given problem. The third stage is the implicitly processed via a back propagation feature exists in the neuro-fuzzy module. Place and Duration of Study: Evaluation and Analysis of Hospital Disaster Preparedness in Jeddah for six months. Methodology: There are six factors have been utilized in the Adaptive Neural Fuzzy Inference module that covers the second stage (Task Analysis Module) of the proposed system alongside with the back propagation process. The training will be based on gathered surveyed data. The purpose of the training is to adjust the model parameters, particularly the input membership function parameters, and the corresponding output values. Results: After training the model with proper data, a clear target-oriented towards the best usage of knowledge will take a place. The developed six modules for the second stage with different types of input/output membership functions and trained an input array. The modules are compared based on their ability to train with lowest error values. The Gaussian membership function input with either constant or linear pairing output membership function was the best choice for the proposed system to be adopted in its second stage which is Task Analysis Module. Conclusion: This model can be utilized in firms, societies or even in individuals’ life events. The context of knowledge as one of the six factors affecting the knowledge valuation process is the most important factor due to its high changes were more noticeable than others.