領域表現に基づいた四項類推を行なうニューラルネットワーク

DOI Web Site Web Site 被引用文献1件 参考文献20件

書誌事項

タイトル別名
  • A Novel Neural Network for Four-Term Analogy based on Area Representation
  • リョウイキ ヒョウゲン ニ モトヅイタ 4コウ ルイスイ オ オコナウ ニューラル ネットワーク

この論文をさがす

抄録

Knowledge representation is important in the information processing. The local representation and the distributed representation are well known. Recently, area representation has attracted much attention because it can preserve advantages of each method. In this paper, 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 the 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 the followings: (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; (4) the network is robust for the lack of connections.

収録刊行物

被引用文献 (1)*注記

もっと見る

参考文献 (20)*注記

もっと見る

キーワード

詳細情報 詳細情報について

問題の指摘

ページトップへ