REASONING ON DOMAIN KNOWLEDGE LEVEL IN HUMAN-COMPUTER INTERACTION

This paper proposes an innovative approach for dynamically analyzing a user's dialog behavior and inferring a user's domain knowledge level simultaneously that combines neural networks, fuzzy cognitive maps, an d fuzzy production rules. Further, this approach supports more coopera tive human-computer interaction through dialog adaptation. Furthermore , when the user's knowledge level and problem-solving capability are i nferred more accurately, there is more assurance that the system's int eraction strategy can match more closely to the user's style. This res earch implements a neural network for classifying a user's performance pattern using UNIX file security commands. Input and output informati on that relate to a fuzzy cognitive map and fuzzy production rules are explained.