A Concepts-of-Sentences Associative Neural Network

This paper proposes a new neural network (the concepts-of-sentences associative neural network, CSANN) which performs memory and recall of sentences represented by a semantic network, as an approach toward natural language processing. The semantic network is represented in terms of the triples representation of concepts. The triples representation of concepts consists of concepts linked by relations in sentences represented by natural language. CSANN handles sentence data, which are difficult to handle since the data size is not unique, by decomposing the data into triples representations of concepts and integrating them into the semantic network format. It is verified by computer simulation that the proposed network can store sentences and recall sentences even if the input information is incomplete. Thus, the effectiveness of the proposed network in natural language processing is demonstrated.