Towards an Agent-Based Knowledge Management System
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In this paper, we propose a knowledge management system that employs agents and case-based reasoning to extract tacit knowledge and support organizational learning and decision making at the level of individual workers, group workers and the whole organization. Agents will perform the tasks of inquiry, investigation, sharing and updating of knowledge bases, including previous similar cases, in order to help in finding the required knowledge for a specific problem. We have applied the system to develop a banking training assistant system and have run several experiments to measure a number of functionalities such as reliability, efficiency, the impact of weight parameters on extracted results, and the degree of match between the results produced by our system and the opinions of randomly selected experts in the chosen application.
KeywordsKnowledge Management Case-Based Reasoning Multi-Agent
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