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
Link To Document :
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