A Concepts-of-Sentences Associative Neural Network

Hitoshi Tanaka, Jingtao Huang, Masafumi Hagiwara

研究成果: Article査読

抄録

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.

本文言語English
ページ(範囲)43-54
ページ数12
ジャーナルSystems and Computers in Japan
34
11
DOI
出版ステータスPublished - 2003 10月 1

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • 情報システム
  • ハードウェアとアーキテクチャ
  • 計算理論と計算数学

フィンガープリント

「A Concepts-of-Sentences Associative Neural Network」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル