• DocumentCode
    2772619
  • Title

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

  • Author

    Sagara, Tsukasa ; Hagiwara, Masafumi

  • Author_Institution
    Grad. Sch. of Sci. & Technol., Keio Univ., Yokohama, Japan
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    1
  • Lastpage
    7
  • Abstract
    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. The proposed network is composed of 3 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 play an important role to process the knowledge units properly. The Dictionary Network also plays an important role as a knowledge based. 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.
  • Keywords
    content-addressable storage; knowledge based systems; natural language processing; neural nets; question answering (information retrieval); artificial intelligence; associative memory; deep case layer; dictionary network; knowledge based system; knowledge layer; knowledge units; metaphor understanding; natural language neural network; question-answering system; sentence layer; Algorithm design and analysis; Dictionaries; Programmable logic arrays; Reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2012 International Joint Conference on
  • Conference_Location
    Brisbane, QLD
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4673-1488-6
  • Electronic_ISBN
    2161-4393
  • Type

    conf

  • DOI
    10.1109/IJCNN.2012.6252553
  • Filename
    6252553