Natural language neural network and its application to question-answering system

Tsukasa Sagara, Masafumi Hagiwara

研究成果: Article査読

37 被引用数 (Scopus)

抄録

This paper proposes a novel neural network to treat natural language. Most of the conventional neural networks can only process sentences consisted of a few words, and their applications are very simple such as metaphor understanding. The proposed network can process many complicated sentences and can be used as an associative memory and a question-answering system for factoid questions. The proposed network is composed of three layers and one network: Sentence Layer, Knowledge Layer, Deep Case Layer and Dictionary Network. The input sentences are divided into knowledge units and stored in the Knowledge Layer. The Deep Case Layer plays an important role in processing the knowledge units properly. The Dictionary Network also plays an important role as a knowledge base. We have carried out several experiments and they have shown that the proposed neural network has superior performances as an associative memory and a question-answering system. Especially as a question-answering system, the performance is very close to the elaborated system based on artificial intelligence.

本文言語English
ページ(範囲)201-208
ページ数8
ジャーナルNeurocomputing
142
DOI
出版ステータスPublished - 2014 10月 22

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 認知神経科学
  • 人工知能

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