Natural language processing neural network for recall and inference

Tsukasa Sagara, Masafumi Hagiwara

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

In this paper, we propose a novel neural network which can learn knowledge from natural language documents and can perform recall and inference. The proposed network has a sentence layer, a knowledge layer, ten kinds of deep case layers and a dictionary layer. In the network learning step, connections are updated based on Hebb's learning rule. The proposed network can handle a complicated sentence by incorporating the deep case layers and get unlearned knowledge from the dictionary layer. In the dictionary layer, Goi-Taikei, containing 400,000 words dictionary, is employed. Two kinds of experiments were carried out by using goo encyclopedia and Wikipedia as knowledge sources. Superior performance of the proposed neural network has been confirmed.

本文言語English
ホスト出版物のタイトルArtificial Neural Networks, ICANN 2010 - 20th International Conference, Proceedings
ページ286-289
ページ数4
PART 3
DOI
出版ステータスPublished - 2010 11 8
イベント20th International Conference on Artificial Neural Networks, ICANN 2010 - Thessaloniki, Greece
継続期間: 2010 9 152010 9 18

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
番号PART 3
6354 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other20th International Conference on Artificial Neural Networks, ICANN 2010
CountryGreece
CityThessaloniki
Period10/9/1510/9/18

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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