• DocumentCode
    530464
  • Title

    Quantized peer review based on semantic neural network

  • Author

    Pang, Huanli ; Liu, Le ; Wu, Qiong

  • Author_Institution
    Coll. of Comput. Sci. & Eng., Changchun Univ. of Technol., Changchun, China
  • Volume
    1
  • fYear
    2010
  • fDate
    24-26 Aug. 2010
  • Firstpage
    169
  • Lastpage
    171
  • Abstract
    Peer review as an evaluation of paper quality of “Sciencepaper Online”, it is an important link of its quantity. Due to the peer review is natural language, use semantic neural network quantized peer review is put forward in this paper. That, parsing the surface semantic analysis of peer review to establish the semantic neural network, and the deep-seated semantic computing of peer review, win the quantized result finally.
  • Keywords
    natural languages; neural nets; peer-to-peer computing; program compilers; natural language; quantized peer review; sciencepaper online paper quality; semantic neural network; surface semantic analysis; Biological neural networks; Book reviews; Humans; natural language understanding; peer review; the deep-seated semantic; the surface semantic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-4244-7957-3
  • Type

    conf

  • DOI
    10.1109/CMCE.2010.5609627
  • Filename
    5609627