A novel neural network for four-term analogy based on area representation

We propose a novel neural network for four-term analogy based on area representation. It can deal with four-term analogy such as “teacher: student=doctor: ?”. The proposed network is composed of three map layers and an input layer. The area representation method based on Kohonen feature map (KFM) is employed in order to represent knowledge, so that similar concepts are mapped in nearer area in the map layer. The proposed mechanism in the map layer can realize the movement of the excited area to the near area. We carried out some computer simulations and confirmed as follows: 1) similar concepts are mapped in the nearer area in the map layer; 2) the excited area moves among similar concepts; 3) the proposed network realizes four-term analogy; and 4) the network is robust for the lack of connections