Knowledge processing system using Kohonen feature map associative memory with refractoriness based on area representation

In this paper, we propose a knowledge processing system using Kohonen feature map associative memory with refractoriness based on area representation. The proposed system is based on the Kohonen feature map associative memory with refractoriness based on area representation. In the conventional Kohonen feature map associative memory, only one-to-one associations can be realized. In contrast, one-to-many associations are realized by the refractoriness of neurons in the Map Layer in the Kohonen feature map associative memory with refractoriness based on area representation. In this research, the Kohonen feature map associative memory with refractoriness based on area representation is applied to knowledge processing in which the knowledge is represented in a form of semantic network. The proposed system has the following features: (1) it can deal with the knowledge which is represented in a form of semantic network; (2) it can deal with characteristics inheritance; (3) it is robust for noisy input. We carried out a series of computer experiment and confirmed the effectiveness of the proposed system.