Memorization and Reasoning of Semantic Network Using Paired-Associate Mapping of Patterns

概要

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In knowledge engineering, there is a semantic network as one method expressing knowledge. Inheritance of properties is possible for a semantic network, and it is a directed graph which consists of nodes and links. Memorizing a semantic network and reasoning there are usually performed by manipulating symbols. A method of memorizing a semantic network and reasoning can be performed by pattern processing is presented here. In other words, it is shown that memory action and reasoning of a semantic network can be performed using model-construction operator T , similarity-measure function SM , and a paired-associate mapping A suggested by S,Suzuki. The five advantages are as follows :(1) The concept and the property memorized by adoption of pattern expression have been easily expressed by the linear-predictive-coefficient vector of the pronounced sound. (2) The concept memorized and the property became strong to noise by adoption of a pattern model. (3) In two phases of memorizing and reasoning made by the association, it became strong to noise by adoption of the paired-associate mapping. (4) In the reasoning phase by association, it became strong to noise by adoption of the similarity-measure function. (5) It can simply perform adding to a semantic network new triple that consists of concept 1, property, and concept 2 by easy correction of the paired-associate mapping and the similarity-measure function.