Selective information retrieval from hierarchical associative knowledge learning memory

For the purpose of building the efficient information system in the dynamic environment, it is necessary to develop the well structured intelligent system which has the mechanism of automatic knowledge acquisition, inference and extraction. It must also have a selective mechanism which can retrieve the information by the selecting factor as much as a user wants, because a user doesn't need all the associated data in the memory. In this paper, we propose Hierarchical Associative system with selective Information retrieval mechanism considering the above functions. We applied this system to the area for estimating the purchasing degree from the customer's tastes, the pattern of commodities and evaluation of a company.